diff --git a/mlflow/catboost.py b/mlflow/catboost.py
index a3af6e1fd3634..cb9eb50b7d4ff 100644
--- a/mlflow/catboost.py
+++ b/mlflow/catboost.py
@@ -13,6 +13,8 @@
     https://catboost.ai/docs/concepts/python-reference_catboost_save_model.html
 .. _CatBoostClassifier:
     https://catboost.ai/docs/concepts/python-reference_catboostclassifier.html
+.. _CatBoostRanker:
+    https://catboost.ai/docs/concepts/python-reference_catboostranker.html
 .. _CatBoostRegressor:
     https://catboost.ai/docs/concepts/python-reference_catboostregressor.html
 """
@@ -90,7 +92,7 @@ def save_model(
     Save a CatBoost model to a path on the local file system.
 
     :param cb_model: CatBoost model (an instance of `CatBoost`_, `CatBoostClassifier`_,
-                     or `CatBoostRegressor`_) to be saved.
+                    `CatBoostRanker`_, or `CatBoostRegressor`_) to be saved.
     :param path: Local path where the model is to be saved.
     :param conda_env: {{ conda_env }}
     :param code_paths: A list of local filesystem paths to Python file dependencies (or directories
@@ -209,7 +211,7 @@ def log_model(
     Log a CatBoost model as an MLflow artifact for the current run.
 
     :param cb_model: CatBoost model (an instance of `CatBoost`_, `CatBoostClassifier`_,
-                     or `CatBoostRegressor`_) to be saved.
+                    `CatBoostRanker`_, or `CatBoostRegressor`_) to be saved.
     :param artifact_path: Run-relative artifact path.
     :param conda_env: {{ conda_env }}
     :param code_paths: A list of local filesystem paths to Python file dependencies (or directories
@@ -269,6 +271,13 @@ def _init_model(model_type):
 
     model_types = {c.__name__: c for c in [CatBoost, CatBoostClassifier, CatBoostRegressor]}
 
+    try:
+        from catboost import CatBoostRanker
+
+        model_types[CatBoostRanker.__name__] = CatBoostRanker
+    except ImportError:
+        pass
+
     if model_type not in model_types:
         raise TypeError(
             "Invalid model type: '{}'. Must be one of {}".format(
@@ -317,7 +326,7 @@ def load_model(model_uri, dst_path=None):
                      This directory must already exist. If unspecified, a local output
                      path will be created.
 
-    :return: A CatBoost model (an instance of `CatBoost`_, `CatBoostClassifier`_,
+    :return: A CatBoost model (an instance of `CatBoost`_, `CatBoostClassifier`_, `CatBoostRanker`_,
              or `CatBoostRegressor`_)
     """
     local_model_path = _download_artifact_from_uri(artifact_uri=model_uri, output_path=dst_path)
diff --git a/tests/catboost/test_catboost_model_export.py b/tests/catboost/test_catboost_model_export.py
index 87e29389a0212..2c6381442240d 100644
--- a/tests/catboost/test_catboost_model_export.py
+++ b/tests/catboost/test_catboost_model_export.py
@@ -1,5 +1,6 @@
 from collections import namedtuple
 from unittest import mock
+from packaging.version import Version
 import os
 import pytest
 import yaml
@@ -91,6 +92,32 @@ def test_init_model(model_type):
     assert model.__class__.__name__ == model_type
 
 
+@pytest.mark.skipif(
+    Version(cb.__version__) < Version("0.26.0"),
+    reason="catboost < 0.26.0 does not support CatBoostRanker",
+)
+def test_log_catboost_ranker():
+    """
+    This is a separate test for the CatBoostRanker model.
+    It is separate since the ranking task requires a group_id column which makes the code different.
+    """
+    # the ranking task requires setting a group_id
+    # we are creating a dummy group_id here that doesn't make any sense for the Iris dataset,
+    # but is ok for testing if the code is running correctly
+    X, y = get_iris()
+    dummy_group_id = np.arange(len(X)) % 3
+    dummy_group_id.sort()
+
+    model = cb.CatBoostRanker(**MODEL_PARAMS, subsample=1.0)
+    model.fit(X, y, group_id=dummy_group_id)
+
+    with mlflow.start_run():
+        model_info = mlflow.catboost.log_model(model, "model")
+        loaded_model = mlflow.catboost.load_model(model_info.model_uri)
+        assert isinstance(loaded_model, cb.CatBoostRanker)
+        np.testing.assert_array_almost_equal(model.predict(X), loaded_model.predict(X))
+
+
 def test_init_model_throws_for_invalid_model_type():
     with pytest.raises(TypeError, match="Invalid model type"):
         mlflow.catboost._init_model("unsupported")