diff --git a/poetry.lock b/poetry.lock
index d250da72e0..3d5ec7b00f 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,4 @@
-# This file is automatically @generated by Poetry 1.8.5 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand.
 
 [[package]]
 name = "annotated-types"
@@ -46,13 +46,13 @@ trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "apify"
-version = "2.2.0"
+version = "2.2.1"
 description = "Apify SDK for Python"
 optional = true
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "apify-2.2.0-py3-none-any.whl", hash = "sha256:fb3597de8a2ee1dc7ac64af4d84e875c6c9ef20f68392138d764af3e3a763f96"},
-    {file = "apify-2.2.0.tar.gz", hash = "sha256:784d01c8385dd0ee07f6055bfb232893a6a59947e929d91de4cd08c05021af94"},
+    {file = "apify-2.2.1-py3-none-any.whl", hash = "sha256:60b190d6e7d438d2ccbeeb40151adcbbd1adfb3bf85936fa01c37e3fbb8e2edb"},
+    {file = "apify-2.2.1.tar.gz", hash = "sha256:9a30828e5f908c020e85fc14f70c74e890ab1b20157ce20b50d199564b12d649"},
 ]
 
 [package.dependencies]
@@ -1054,13 +1054,13 @@ testing = ["hatch", "pre-commit", "pytest", "tox"]
 
 [[package]]
 name = "executing"
-version = "2.1.0"
+version = "2.2.0"
 description = "Get the currently executing AST node of a frame, and other information"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "executing-2.1.0-py2.py3-none-any.whl", hash = "sha256:8d63781349375b5ebccc3142f4b30350c0cd9c79f921cde38be2be4637e98eaf"},
-    {file = "executing-2.1.0.tar.gz", hash = "sha256:8ea27ddd260da8150fa5a708269c4a10e76161e2496ec3e587da9e3c0fe4b9ab"},
+    {file = "executing-2.2.0-py2.py3-none-any.whl", hash = "sha256:11387150cad388d62750327a53d3339fad4888b39a6fe233c3afbb54ecffd3aa"},
+    {file = "executing-2.2.0.tar.gz", hash = "sha256:5d108c028108fe2551d1a7b2e8b713341e2cb4fc0aa7dcf966fa4327a5226755"},
 ]
 
 [package.extras]
@@ -1196,13 +1196,13 @@ hyperframe = ">=6.0,<7"
 
 [[package]]
 name = "hpack"
-version = "4.0.0"
-description = "Pure-Python HPACK header compression"
+version = "4.1.0"
+description = "Pure-Python HPACK header encoding"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.9"
 files = [
-    {file = "hpack-4.0.0-py3-none-any.whl", hash = "sha256:84a076fad3dc9a9f8063ccb8041ef100867b1878b25ef0ee63847a5d53818a6c"},
-    {file = "hpack-4.0.0.tar.gz", hash = "sha256:fc41de0c63e687ebffde81187a948221294896f6bdc0ae2312708df339430095"},
+    {file = "hpack-4.1.0-py3-none-any.whl", hash = "sha256:157ac792668d995c657d93111f46b4535ed114f0c9c8d672271bbec7eae1b496"},
+    {file = "hpack-4.1.0.tar.gz", hash = "sha256:ec5eca154f7056aa06f196a557655c5b009b382873ac8d1e66e79e87535f1dca"},
 ]
 
 [[package]]
@@ -1277,24 +1277,24 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "hyperframe"
-version = "6.0.1"
-description = "HTTP/2 framing layer for Python"
+version = "6.1.0"
+description = "Pure-Python HTTP/2 framing"
 optional = false
-python-versions = ">=3.6.1"
+python-versions = ">=3.9"
 files = [
-    {file = "hyperframe-6.0.1-py3-none-any.whl", hash = "sha256:0ec6bafd80d8ad2195c4f03aacba3a8265e57bc4cff261e802bf39970ed02a15"},
-    {file = "hyperframe-6.0.1.tar.gz", hash = "sha256:ae510046231dc8e9ecb1a6586f63d2347bf4c8905914aa84ba585ae85f28a914"},
+    {file = "hyperframe-6.1.0-py3-none-any.whl", hash = "sha256:b03380493a519fce58ea5af42e4a42317bf9bd425596f7a0835ffce80f1a42e5"},
+    {file = "hyperframe-6.1.0.tar.gz", hash = "sha256:f630908a00854a7adeabd6382b43923a4c4cd4b821fcb527e6ab9e15382a3b08"},
 ]
 
 [[package]]
 name = "identify"
-version = "2.6.5"
+version = "2.6.6"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "identify-2.6.5-py2.py3-none-any.whl", hash = "sha256:14181a47091eb75b337af4c23078c9d09225cd4c48929f521f3bf16b09d02566"},
-    {file = "identify-2.6.5.tar.gz", hash = "sha256:c10b33f250e5bba374fae86fb57f3adcebf1161bce7cdf92031915fd480c13bc"},
+    {file = "identify-2.6.6-py2.py3-none-any.whl", hash = "sha256:cbd1810bce79f8b671ecb20f53ee0ae8e86ae84b557de31d89709dc2a48ba881"},
+    {file = "identify-2.6.6.tar.gz", hash = "sha256:7bec12768ed44ea4761efb47806f0a41f86e7c0a5fdf5950d4648c90eca7e251"},
 ]
 
 [package.extras]
@@ -1316,13 +1316,13 @@ all = ["flake8 (>=7.1.1)", "mypy (>=1.11.2)", "pytest (>=8.3.2)", "ruff (>=0.6.2
 
 [[package]]
 name = "importlib-metadata"
-version = "8.5.0"
+version = "8.6.1"
 description = "Read metadata from Python packages"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "importlib_metadata-8.5.0-py3-none-any.whl", hash = "sha256:45e54197d28b7a7f1559e60b95e7c567032b602131fbd588f1497f47880aa68b"},
-    {file = "importlib_metadata-8.5.0.tar.gz", hash = "sha256:71522656f0abace1d072b9e5481a48f07c138e00f079c38c8f883823f9c26bd7"},
+    {file = "importlib_metadata-8.6.1-py3-none-any.whl", hash = "sha256:02a89390c1e15fdfdc0d7c6b25cb3e62650d0494005c97d6f148bf5b9787525e"},
+    {file = "importlib_metadata-8.6.1.tar.gz", hash = "sha256:310b41d755445d74569f993ccfc22838295d9fe005425094fad953d7f15c8580"},
 ]
 
 [package.dependencies]
@@ -1334,7 +1334,7 @@ cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
 enabler = ["pytest-enabler (>=2.2)"]
 perf = ["ipython"]
-test = ["flufl.flake8", "importlib-resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
+test = ["flufl.flake8", "importlib_resources (>=1.3)", "jaraco.test (>=5.4)", "packaging", "pyfakefs", "pytest (>=6,!=8.1.*)", "pytest-perf (>=0.9.2)"]
 type = ["pytest-mypy"]
 
 [[package]]
@@ -1417,6 +1417,16 @@ qtconsole = ["qtconsole"]
 test = ["pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath"]
 test-extra = ["curio", "matplotlib (!=3.2.0)", "nbformat", "numpy (>=1.22)", "pandas", "pickleshare", "pytest (<7.1)", "pytest-asyncio (<0.22)", "testpath", "trio"]
 
+[[package]]
+name = "jaro-winkler"
+version = "2.0.3"
+description = "Original, standard and customisable versions of the Jaro-Winkler functions."
+optional = true
+python-versions = "*"
+files = [
+    {file = "jaro_winkler-2.0.3-py3-none-any.whl", hash = "sha256:9ad42a94eb110351e72dd5b9e0a0f1053b0760761d676f9be35da19ea80d511b"},
+]
+
 [[package]]
 name = "jedi"
 version = "0.19.2"
@@ -1478,6 +1488,17 @@ files = [
     {file = "jmespath-1.0.1.tar.gz", hash = "sha256:90261b206d6defd58fdd5e85f478bf633a2901798906be2ad389150c5c60edbe"},
 ]
 
+[[package]]
+name = "joblib"
+version = "1.4.2"
+description = "Lightweight pipelining with Python functions"
+optional = true
+python-versions = ">=3.8"
+files = [
+    {file = "joblib-1.4.2-py3-none-any.whl", hash = "sha256:06d478d5674cbc267e7496a410ee875abd68e4340feff4490bcb7afb88060ae6"},
+    {file = "joblib-1.4.2.tar.gz", hash = "sha256:2382c5816b2636fbd20a09e0f4e9dad4736765fdfb7dca582943b9c1366b3f0e"},
+]
+
 [[package]]
 name = "lazy-object-proxy"
 version = "1.10.0"
@@ -1799,13 +1820,13 @@ files = [
 
 [[package]]
 name = "more-itertools"
-version = "10.5.0"
+version = "10.6.0"
 description = "More routines for operating on iterables, beyond itertools"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "more-itertools-10.5.0.tar.gz", hash = "sha256:5482bfef7849c25dc3c6dd53a6173ae4795da2a41a80faea6700d9f5846c5da6"},
-    {file = "more_itertools-10.5.0-py3-none-any.whl", hash = "sha256:037b0d3203ce90cca8ab1defbbdac29d5f993fc20131f3664dc8d6acfa872aef"},
+    {file = "more-itertools-10.6.0.tar.gz", hash = "sha256:2cd7fad1009c31cc9fb6a035108509e6547547a7a738374f10bd49a09eb3ee3b"},
+    {file = "more_itertools-10.6.0-py3-none-any.whl", hash = "sha256:6eb054cb4b6db1473f6e15fcc676a08e4732548acd47c708f0e179c2c7c01e89"},
 ]
 
 [[package]]
@@ -2030,6 +2051,124 @@ files = [
 deprecated = ">=1.2.0,<2.0.0"
 typing-extensions = ">=3.0.0"
 
+[[package]]
+name = "numpy"
+version = "2.0.2"
+description = "Fundamental package for array computing in Python"
+optional = true
+python-versions = ">=3.9"
+files = [
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+
+[[package]]
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+version = "2.2.2"
+description = "Fundamental package for array computing in Python"
+optional = true
+python-versions = ">=3.10"
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+    {file = "wrapt-1.17.2-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:99039fa9e6306880572915728d7f6c24a86ec57b0a83f6b2491e1d8ab0235b9a"},
+    {file = "wrapt-1.17.2-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:2696993ee1eebd20b8e4ee4356483c4cb696066ddc24bd70bcbb80fa56ff9061"},
+    {file = "wrapt-1.17.2-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:612dff5db80beef9e649c6d803a8d50c409082f1fedc9dbcdfde2983b2025b82"},
+    {file = "wrapt-1.17.2-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:62c2caa1585c82b3f7a7ab56afef7b3602021d6da34fbc1cf234ff139fed3cd9"},
+    {file = "wrapt-1.17.2-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c958bcfd59bacc2d0249dcfe575e71da54f9dcf4a8bdf89c4cb9a68a1170d73f"},
+    {file = "wrapt-1.17.2-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:fc78a84e2dfbc27afe4b2bd7c80c8db9bca75cc5b85df52bfe634596a1da846b"},
+    {file = "wrapt-1.17.2-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:ba0f0eb61ef00ea10e00eb53a9129501f52385c44853dbd6c4ad3f403603083f"},
+    {file = "wrapt-1.17.2-cp39-cp39-musllinux_1_2_i686.whl", hash = "sha256:1e1fe0e6ab7775fd842bc39e86f6dcfc4507ab0ffe206093e76d61cde37225c8"},
+    {file = "wrapt-1.17.2-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:c86563182421896d73858e08e1db93afdd2b947a70064b813d515d66549e15f9"},
+    {file = "wrapt-1.17.2-cp39-cp39-win32.whl", hash = "sha256:f393cda562f79828f38a819f4788641ac7c4085f30f1ce1a68672baa686482bb"},
+    {file = "wrapt-1.17.2-cp39-cp39-win_amd64.whl", hash = "sha256:36ccae62f64235cf8ddb682073a60519426fdd4725524ae38874adf72b5f2aeb"},
+    {file = "wrapt-1.17.2-py3-none-any.whl", hash = "sha256:b18f2d1533a71f069c7f82d524a52599053d4c7166e9dd374ae2136b7f40f7c8"},
+    {file = "wrapt-1.17.2.tar.gz", hash = "sha256:41388e9d4d1522446fe79d3213196bd9e3b301a336965b9e27ca2788ebd122f3"},
 ]
 
 [[package]]
@@ -3774,7 +4134,8 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\
 cffi = ["cffi (>=1.11)"]
 
 [extras]
-all = ["beautifulsoup4", "curl-cffi", "html5lib", "lxml", "parsel", "playwright"]
+adaptive-playwright = ["jaro-winkler", "playwright", "scikit-learn", "scikit-learn"]
+all = ["beautifulsoup4", "curl-cffi", "html5lib", "jaro-winkler", "lxml", "parsel", "playwright", "scikit-learn", "scikit-learn"]
 beautifulsoup = ["beautifulsoup4", "html5lib", "lxml"]
 curl-impersonate = ["curl-cffi"]
 parsel = ["parsel"]
@@ -3783,4 +4144,4 @@ playwright = ["playwright"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "74d60baf6f6e8c7559243ce5293be0e418c0ee03835dd600e45eb6f2b6840b6d"
+content-hash = "b395f6bad80841f3ecacf8d310fe3f8c4aa881c8454cc7ca9007af4c28a9c9b3"
diff --git a/pyproject.toml b/pyproject.toml
index 61b0c768a0..3c6f187f2b 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -52,6 +52,7 @@ eval-type-backport = ">=0.2.0"
 html5lib = { version = ">=1.0", optional = true }
 httpx = {version = ">=0.27.0", extras = ["brotli", "http2", "zstd"]}
 inquirer = ">=3.3.0"
+jaro-winkler = { version = ">=2.0.3", optional = true }
 lxml = { version = ">=5.2.0", optional = true }
 more_itertools = ">=10.2.0"
 parsel = { version = ">=1.9.0", optional = true }
@@ -62,6 +63,10 @@ pydantic = ">=2.8.1, !=2.10.0, !=2.10.1, !=2.10.2"
 # https://github.com/apify/crawlee-python/issues/814
 pydantic-settings = ">=2.2.0 <2.7.0"
 pyee = ">=9.0.0"
+scikit-learn =  [
+    {version = ">=1.6.0", python = ">=3.10", optional = true},
+    {version = "==1.5.2", python = "==3.9", optional = true}
+]
 sortedcollections = ">=2.1.0"
 tldextract = ">=5.1.0"
 typer = ">=0.12.0"
@@ -92,7 +97,10 @@ types-psutil = "~5.9.5.20240205"
 types-python-dateutil = "~2.9.0.20240316"
 
 [tool.poetry.extras]
-all = ["beautifulsoup4", "curl-cffi", "lxml", "html5lib", "parsel", "playwright"]
+# Support for re-using groups in other groups https://peps.python.org/pep-0735/ in poetry:
+# https://github.com/python-poetry/poetry/issues/9751
+adaptive-playwright = ["jaro-winkler", "playwright", "scikit-learn"]
+all = ["beautifulsoup4", "curl-cffi", "html5lib", "jaro-winkler", "lxml", "parsel", "playwright", "scikit-learn"]
 beautifulsoup = ["beautifulsoup4", "lxml", "html5lib"]
 curl-impersonate = ["curl-cffi"]
 playwright = ["playwright"]
@@ -207,8 +215,10 @@ warn_unused_ignores = true
 [[tool.mypy.overrides]]
 # Example codes are sometimes showing integration of crawlee with external tool, which is not dependency of crawlee.
 module = [
-    "apify",    # Example code shows integration of apify and crawlee.
-    "camoufox", # Example code shows integration of camoufox and crawlee.
+    "apify",                # Example code shows integration of apify and crawlee.
+    "camoufox",             # Example code shows integration of camoufox and crawlee.
+    "jaro",                 # Untyped and stubs not available
+    "sklearn.linear_model", # Untyped and stubs not available
 ]
 ignore_missing_imports = true
 
diff --git a/src/crawlee/crawlers/_adaptive_playwright/__init__.py b/src/crawlee/crawlers/_adaptive_playwright/__init__.py
new file mode 100644
index 0000000000..e69de29bb2
diff --git a/src/crawlee/crawlers/_adaptive_playwright/_rendering_type_predictor.py b/src/crawlee/crawlers/_adaptive_playwright/_rendering_type_predictor.py
new file mode 100644
index 0000000000..653e7adc60
--- /dev/null
+++ b/src/crawlee/crawlers/_adaptive_playwright/_rendering_type_predictor.py
@@ -0,0 +1,172 @@
+from abc import ABC, abstractmethod
+from collections import defaultdict
+from dataclasses import dataclass
+from itertools import zip_longest
+from statistics import mean
+from typing import Literal
+from urllib.parse import urlparse
+
+from jaro import jaro_winkler_metric
+from sklearn.linear_model import LogisticRegression
+from typing_extensions import override
+
+from crawlee import Request
+
+UrlComponents = list[str]
+RenderingType = Literal['static', 'client only']
+FeatureVector = tuple[float, float]
+
+
+@dataclass(frozen=True)
+class RenderingTypePrediction:
+    rendering_type: RenderingType
+    detection_probability_recommendation: float
+
+
+class RenderingTypePredictor(ABC):
+    @abstractmethod
+    def predict(self, request: Request) -> RenderingTypePrediction:
+        """Get `RenderingTypePrediction` based on the input request.
+
+        Args:
+            request: `Request` instance for which the prediction is made.
+        """
+
+    @abstractmethod
+    def store_result(self, request: Request, rendering_type: RenderingType) -> None:
+        """Store prediction results and retrain the model.
+
+        Args:
+            request: Used request.
+            rendering_type: Known suitable `RenderingType`.
+        """
+
+
+class DefaultRenderingTypePredictor(RenderingTypePredictor):
+    """Stores rendering type for previously crawled URLs and predicts the rendering type for unvisited urls.
+
+    `RenderingTypePredictor` implementation based on logistic regression:
+    https://scikit-learn.org/stable/modules/generated/sklearn.linear_model.LogisticRegression.html
+    """
+
+    def __init__(self, detection_ratio: float = 0.1) -> None:
+        """A default constructor.
+
+        Args:
+            detection_ratio: A number between 0 and 1 that determines the desired ratio of rendering type detections.
+        """
+        self._rendering_type_detection_results: dict[RenderingType, dict[str, list[UrlComponents]]] = {
+            'static': defaultdict(list),
+            'client only': defaultdict(list),
+        }
+        self._model = LogisticRegression(max_iter=1000)
+        self._detection_ratio = max(0, min(1, detection_ratio))
+
+        # Used to increase detection probability recommendation for initial recommendations of each label.
+        # Reaches 1 (no additional increase) after n samples of specific label is already present in
+        # `self._rendering_type_detection_results`.
+        n = 3
+        self._labels_coefficients: dict[str, float] = defaultdict(lambda: n + 2)
+
+    @override
+    def predict(self, request: Request) -> RenderingTypePrediction:
+        """Get `RenderingTypePrediction` based on the input request.
+
+        Args:
+            request: `Request` instance for which the prediction is made.
+        """
+        similarity_threshold = 0.1  #  Prediction probability difference threshold to consider prediction unreliable.
+        label = request.label or ''
+
+        if self._rendering_type_detection_results['static'] or self._rendering_type_detection_results['client only']:
+            url_feature = self._calculate_feature_vector(get_url_components(request.url), label)
+            # Are both calls expensive?
+            prediction = self._model.predict([url_feature])[0]
+            probability = self._model.predict_proba([url_feature])[0]
+
+            if abs(probability[0] - probability[1]) < similarity_threshold:
+                # Prediction not reliable.
+                detection_probability_recommendation = 1.0
+            else:
+                detection_probability_recommendation = self._detection_ratio
+                # Increase recommendation for uncommon labels.
+                detection_probability_recommendation *= self._labels_coefficients[label]
+
+            return RenderingTypePrediction(
+                rendering_type=('client only', 'static')[int(prediction)],
+                detection_probability_recommendation=detection_probability_recommendation,
+            )
+        # No data available yet.
+        return RenderingTypePrediction(rendering_type='client only', detection_probability_recommendation=1)
+
+    @override
+    def store_result(self, request: Request, rendering_type: RenderingType) -> None:
+        """Store prediction results and retrain the model.
+
+        Args:
+            request: Used `Request` instance.
+            rendering_type: Known suitable `RenderingType` for the used `Request` instance.
+        """
+        label = request.label or ''
+        self._rendering_type_detection_results[rendering_type][label].append(get_url_components(request.url))
+        if self._labels_coefficients[label] > 1:
+            self._labels_coefficients[label] -= 1
+        self._retrain()
+
+    def _retrain(self) -> None:
+        x: list[FeatureVector] = [(0, 1), (1, 0)]
+        y: list[float] = [0, 1]
+
+        for rendering_type, urls_by_label in self._rendering_type_detection_results.items():
+            encoded_rendering_type = 1 if rendering_type == 'static' else 0
+            for label, urls in urls_by_label.items():
+                for url_components in urls:
+                    x.append(self._calculate_feature_vector(url_components, label))
+                    y.append(encoded_rendering_type)
+
+        self._model.fit(x, y)
+
+    def _calculate_mean_similarity(self, url: UrlComponents, label: str, rendering_type: RenderingType) -> float:
+        if not self._rendering_type_detection_results[rendering_type][label]:
+            return 0
+        return mean(
+            calculate_url_similarity(url, known_url_components)
+            for known_url_components in self._rendering_type_detection_results[rendering_type][label]
+        )
+
+    def _calculate_feature_vector(self, url: UrlComponents, label: str) -> tuple[float, float]:
+        return (
+            self._calculate_mean_similarity(url, label, 'static'),
+            self._calculate_mean_similarity(url, label, 'client only'),
+        )
+
+
+def get_url_components(url: str) -> UrlComponents:
+    """Get list of url components where first component is host name."""
+    parsed_url = urlparse(url)
+    if parsed_url.path:
+        return [parsed_url.netloc, *parsed_url.path.strip('/').split('/')]
+    return [parsed_url.netloc]
+
+
+def calculate_url_similarity(url_1: UrlComponents, url_2: UrlComponents) -> float:
+    """Calculate url similarity based on host name and path components similarity.
+
+    Return 0 if different host names.
+    Compare path components using jaro-wrinkler method and assign 1 or 0 value based on similarity_cutoff for each
+    path component. Return their weighted average.
+    """
+    # Anything with jaro_winkler_metric less than this value is considered completely different,
+    # otherwise considered the same.
+    similarity_cutoff = 0.8
+
+    if (url_1[0] != url_2[0]) or not url_1 or not url_2:
+        return 0
+    if url_1 == url_2:
+        return 1
+
+    # Each additional path component from longer path is compared to empty string.
+    return mean(
+        1 if jaro_winkler_metric(path_1, path_2) > similarity_cutoff else 0
+        for path_1, path_2 in zip_longest(url_1[1:], url_2[1:], fillvalue='')
+    )
diff --git a/tests/unit/crawlers/_adaptive_playwright/test_predictor.py b/tests/unit/crawlers/_adaptive_playwright/test_predictor.py
new file mode 100644
index 0000000000..c54ef0f813
--- /dev/null
+++ b/tests/unit/crawlers/_adaptive_playwright/test_predictor.py
@@ -0,0 +1,139 @@
+from __future__ import annotations
+
+import pytest
+
+from crawlee import Request
+from crawlee.crawlers._adaptive_playwright._rendering_type_predictor import (
+    DefaultRenderingTypePredictor,
+    RenderingType,
+    calculate_url_similarity,
+    get_url_components,
+)
+
+
+@pytest.mark.parametrize('label', ['some label', None])
+@pytest.mark.parametrize(
+    ('url', 'expected_prediction'),
+    [
+        ('http://www.aaa.com/some/stuff/extra', 'static'),
+        ('http://www.aab.com/some/otherstuff', 'static'),
+        ('http://www.aac.com/some', 'static'),
+        ('http://www.ddd.com/some/stuff/extra', 'client only'),
+        ('http://www.dde.com/some/otherstuff', 'client only'),
+        ('http://www.ddf.com/some', 'client only'),
+    ],
+)
+def ictor_same_label(url: str, expected_prediction: RenderingType, label: str | None) -> None:
+    predictor = DefaultRenderingTypePredictor()
+
+    learning_inputs: tuple[tuple[str, RenderingType], ...] = (
+        ('http://www.aaa.com/some/stuff', 'static'),
+        ('http://www.aab.com/some/stuff', 'static'),
+        ('http://www.aac.com/some/stuff', 'static'),
+        ('http://www.ddd.com/some/stuff', 'client only'),
+        ('http://www.dde.com/some/stuff', 'client only'),
+        ('http://www.ddf.com/some/stuff', 'client only'),
+    )
+
+    # Learn from small set
+    for learned_url, rendering_type in learning_inputs:
+        predictor.store_result(Request.from_url(url=learned_url, label=label), rendering_type=rendering_type)
+
+    assert predictor.predict(Request.from_url(url=url, label=label)).rendering_type == expected_prediction
+
+
+def test_predictor_new_label_increased_detection_probability_recommendation() -> None:
+    """Test that urls of uncommon labels have increased detection recommendation.
+
+    This increase should gradually drop as the predictor learns more data with this label."""
+    detection_ratio = 0.01
+    label = 'some label'
+    predictor = DefaultRenderingTypePredictor(detection_ratio=detection_ratio)
+
+    # Learn first prediction of this label
+    predictor.store_result(Request.from_url(url='http://www.aaa.com/some/stuff', label=label), rendering_type='static')
+    # Increased detection_probability_recommendation
+    prediction = predictor.predict(Request.from_url(url='http://www.aaa.com/some/stuffa', label=label))
+    assert prediction.rendering_type == 'static'
+    assert prediction.detection_probability_recommendation == detection_ratio * 4
+
+    # Learn second prediction of this label
+    predictor.store_result(Request.from_url(url='http://www.aaa.com/some/stuffe', label=label), rendering_type='static')
+    # Increased detection_probability_recommendation
+    prediction = predictor.predict(Request.from_url(url='http://www.aaa.com/some/stuffa', label=label))
+    assert prediction.rendering_type == 'static'
+    assert prediction.detection_probability_recommendation == detection_ratio * 3
+
+    # Learn third prediction of this label
+    predictor.store_result(Request.from_url(url='http://www.aaa.com/some/stuffi', label=label), rendering_type='static')
+    # Increased detection_probability_recommendation
+    prediction = predictor.predict(Request.from_url(url='http://www.aaa.com/some/stuffa', label=label))
+    assert prediction.rendering_type == 'static'
+    assert prediction.detection_probability_recommendation == detection_ratio * 2
+
+    # Learn fourth prediction of this label.
+    predictor.store_result(Request.from_url(url='http://www.aaa.com/some/stuffo', label=label), rendering_type='static')
+    # Label considered stable now. There should be no increase of detection_probability_recommendation.
+    prediction = predictor.predict(Request.from_url(url='http://www.aaa.com/some/stuffa', label=label))
+    assert prediction.rendering_type == 'static'
+    assert prediction.detection_probability_recommendation == detection_ratio
+
+
+def test_unreliable_prediction() -> None:
+    """Test that detection_probability_recommendation for unreliable predictions is 1.
+
+     Creates situation where no learning data of new label is available for the predictor.
+     It's first prediction is not reliable as both options have 50% chance, so it should set maximum
+    detection_probability_recommendation."""
+    learnt_label = 'some label'
+    predictor = DefaultRenderingTypePredictor()
+
+    # Learn two predictions of some label. One of each to make predictor very uncertain.
+    predictor.store_result(
+        Request.from_url(url='http://www.aaa.com/some/stuff', label=learnt_label), rendering_type='static'
+    )
+    predictor.store_result(
+        Request.from_url(url='http://www.aaa.com/some/otherstuff', label=learnt_label), rendering_type='client only'
+    )
+
+    # Predict for new label. Predictor does not have enough information to give any reliable guess and should make it
+    # clear by setting detection_probability_recommendation=1
+    assert (
+        predictor.predict(
+            Request.from_url(url='http://www.unknown.com', label='new label')
+        ).detection_probability_recommendation
+        == 1
+    )
+
+
+def test_no_learning_data_prediction() -> None:
+    """Test that predictor can predict even if it never learnt anything before.
+
+    It should give some prediction, but it has to set detection_probability_recommendation=1"""
+    predictor = DefaultRenderingTypePredictor()
+    assert (
+        predictor.predict(
+            Request.from_url(url='http://www.unknown.com', label='new label')
+        ).detection_probability_recommendation
+        == 1
+    )
+
+
+@pytest.mark.parametrize(
+    ('url_1', 'url_2', 'expected_rounded_similarity'),
+    [
+        (
+            'https://docs.python.org/3/library/itertools.html#itertools.zip_longest',
+            'https://docs.python.org/3.7/library/itertools.html#itertools.zip_longest',
+            0.67,
+        ),
+        ('https://differente.com/same', 'https://differenta.com/same', 0),
+        ('https://same.com/almost_the_same', 'https://same.com/almost_the_sama', 1),
+        ('https://same.com/same/extra', 'https://same.com/same', 0.5),
+    ],
+)
+def test_url_similarity(url_1: str, url_2: str, expected_rounded_similarity: float) -> None:
+    assert (
+        round(calculate_url_similarity(url_1=get_url_components(url_1), url_2=get_url_components(url_2)), 2)
+        == expected_rounded_similarity
+    )