diff --git a/openml/evaluations/__init__.py b/openml/evaluations/__init__.py
index b56d0c2d5..29344b03a 100644
--- a/openml/evaluations/__init__.py
+++ b/openml/evaluations/__init__.py
@@ -1,10 +1,16 @@
 # License: BSD 3-Clause
 
 from .evaluation import OpenMLEvaluation
-from .functions import list_evaluation_measures, list_evaluations, list_evaluations_setups
+from .functions import (
+    list_estimation_procedures,
+    list_evaluation_measures,
+    list_evaluations,
+    list_evaluations_setups,
+)
 
 __all__ = [
     "OpenMLEvaluation",
+    "list_estimation_procedures",
     "list_evaluation_measures",
     "list_evaluations",
     "list_evaluations_setups",
diff --git a/openml/evaluations/functions.py b/openml/evaluations/functions.py
index f4e07c1b8..7516cfa27 100644
--- a/openml/evaluations/functions.py
+++ b/openml/evaluations/functions.py
@@ -2,6 +2,7 @@
 # ruff: noqa: PLR0913
 from __future__ import annotations
 
+import warnings
 from functools import partial
 from itertools import chain
 from typing import TYPE_CHECKING, Literal
@@ -15,6 +16,7 @@
 import openml.utils
 
 if TYPE_CHECKING:
+    from openml.estimation_procedures import OpenMLEstimationProcedure
     from openml.evaluations import OpenMLEvaluation
 
 
@@ -156,18 +158,65 @@ def list_evaluation_measures() -> list[str]:
     return openml._backend.evaluation_measure.list()
 
 
-def list_estimation_procedures() -> list[str]:
-    """Return list of evaluation procedures available.
+@overload
+def list_estimation_procedures(
+    output_format: Literal["dataframe"],
+) -> pd.DataFrame: ...
+
+
+@overload
+def list_estimation_procedures(
+    output_format: Literal["object"],
+) -> dict[int, OpenMLEstimationProcedure]: ...
+
+
+@overload
+def list_estimation_procedures(
+    output_format: None = None,
+) -> list[str]: ...
+
+
+def list_estimation_procedures(
+    output_format: Literal["object", "dataframe"] | None = None,
+) -> list[str] | dict[int, OpenMLEstimationProcedure] | pd.DataFrame:
+    """Return the estimation procedures available on OpenML.
 
     The function performs an API call to retrieve the entire list of
-    evaluation procedures' names that are available.
+    evaluation procedures.
+
+    Parameters
+    ----------
+    output_format : {"object", "dataframe"}, optional
+        The format of the returned procedures. ``"object"`` returns a
+        dictionary mapping procedure IDs to ``OpenMLEstimationProcedure``
+        instances. ``"dataframe"`` returns one row per procedure.
+        If omitted, a list of procedure names is returned for backwards
+        compatibility and a warning is emitted.
 
     Returns
     -------
-    list
+    list[str], dict[int, OpenMLEstimationProcedure], or pandas.DataFrame
+        The available estimation procedures in the requested format.
     """
     result = openml._backend.estimation_procedure.list()
-    return [i.name for i in result]
+
+    if output_format is None:
+        warnings.warn(
+            "The default output will change from a list of names to a dictionary of "
+            "OpenMLEstimationProcedure objects in a future release. Set "
+            "output_format='object' to use the new format.",
+            FutureWarning,
+            stacklevel=2,
+        )
+        return [procedure.name for procedure in result]
+
+    if output_format == "dataframe":
+        return pd.DataFrame.from_records(procedure._to_dict() for procedure in result)
+
+    if output_format == "object":
+        return {procedure.id: procedure for procedure in result}
+
+    raise ValueError("Invalid output format. Only 'object' and 'dataframe' are applicable.")
 
 
 def list_evaluations_setups(
diff --git a/tests/test_evaluations/test_evaluation_functions.py b/tests/test_evaluations/test_evaluation_functions.py
index e15556d7b..a616ea799 100644
--- a/tests/test_evaluations/test_evaluation_functions.py
+++ b/tests/test_evaluations/test_evaluation_functions.py
@@ -1,10 +1,14 @@
 # License: BSD 3-Clause
 from __future__ import annotations
 
+from unittest.mock import patch
+
 import pytest
 
 import openml
 import openml.evaluations
+from openml.estimation_procedures import OpenMLEstimationProcedure
+from openml.tasks import TaskType
 from openml.testing import TestBase
 
 
@@ -239,6 +243,55 @@ def test_list_evaluation_measures(self):
         assert isinstance(measures, list) is True
         assert all(isinstance(s, str) for s in measures) is True
 
+    def test_list_estimation_procedures_default_warns_about_future_change(self):
+        procedures = [
+            OpenMLEstimationProcedure(
+                id=5,
+                task_type_id=TaskType.SUPERVISED_CLASSIFICATION,
+                name="10-fold Crossvalidation",
+                type="crossvalidation",
+            )
+        ]
+        with patch.object(openml._backend.estimation_procedure, "list", return_value=procedures):
+            with pytest.warns(FutureWarning, match="output will change"):
+                result = openml.evaluations.list_estimation_procedures()
+
+        assert result == ["10-fold Crossvalidation"]
+
+    def test_list_estimation_procedures_object(self):
+        procedure = OpenMLEstimationProcedure(
+            id=5,
+            task_type_id=TaskType.SUPERVISED_CLASSIFICATION,
+            name="10-fold Crossvalidation",
+            type="crossvalidation",
+        )
+        with patch.object(openml._backend.estimation_procedure, "list", return_value=[procedure]):
+            result = openml.evaluations.list_estimation_procedures(output_format="object")
+
+        assert result == {5: procedure}
+
+    def test_list_estimation_procedures_dataframe(self):
+        procedures = [
+            OpenMLEstimationProcedure(
+                id=5,
+                task_type_id=TaskType.SUPERVISED_CLASSIFICATION,
+                name="10-fold Crossvalidation",
+                type="crossvalidation",
+            )
+        ]
+        with patch.object(openml._backend.estimation_procedure, "list", return_value=procedures):
+            result = openml.evaluations.list_estimation_procedures(output_format="dataframe")
+
+        assert list(result.columns) == ["id", "task_type_id", "name", "type"]
+        assert result.to_dict("records") == [
+            {
+                "id": 5,
+                "task_type_id": TaskType.SUPERVISED_CLASSIFICATION,
+                "name": "10-fold Crossvalidation",
+                "type": "crossvalidation",
+            }
+        ]
+
     @pytest.mark.production_server()
     def test_list_evaluations_setups_filter_flow(self):
         self.use_production_server()