diff --git a/python/ray/train/batch_predictor.py b/python/ray/train/batch_predictor.py
index 576d14699e5ff..284c2b026347e 100644
--- a/python/ray/train/batch_predictor.py
+++ b/python/ray/train/batch_predictor.py
@@ -3,6 +3,7 @@
 from typing import Any, Dict, Optional, List, Type, Union, Callable
 import pandas as pd
 import numpy as np
+import warnings
 
 import ray
 from ray.air import Checkpoint
@@ -11,12 +12,12 @@
 from ray.data import Dataset, DatasetPipeline, Preprocessor
 from ray.data.context import DataContext
 from ray.train.predictor import Predictor
-from ray.util.annotations import PublicAPI
+from ray.util.annotations import Deprecated
 
 logger = logging.getLogger(__name__)
 
 
-@PublicAPI(stability="beta")
+@Deprecated
 class BatchPredictor:
     """Batch predictor class.
 
@@ -30,6 +31,11 @@ class BatchPredictor:
     def __init__(
         self, checkpoint: Checkpoint, predictor_cls: Type[Predictor], **predictor_kwargs
     ):
+        warnings.warn(
+            "`BatchPredictor` is deprecated. Use `Dataset.map_batches`  instead. To "
+            "learn more, see http://batchinference.io.",
+            DeprecationWarning,
+        )
         self._checkpoint = checkpoint
         # Store as object ref so we only serialize it once for all map workers
         self._checkpoint_ref = ray.put(checkpoint)
diff --git a/python/ray/train/tests/test_batch_predictor.py b/python/ray/train/tests/test_batch_predictor.py
index 1e2f5ef73cf8b..569db17a6b971 100644
--- a/python/ray/train/tests/test_batch_predictor.py
+++ b/python/ray/train/tests/test_batch_predictor.py
@@ -37,6 +37,14 @@ def _transform_numpy(self, np_data):
             return np_data * self.multiplier
 
 
+def test_batch_predictor_warns_deprecation(shutdown_only):
+    with pytest.warns(DeprecationWarning):
+        BatchPredictor.from_checkpoint(
+            Checkpoint.from_dict({"factor": 0}),
+            DummyPredictorFS,
+        )
+
+
 def test_repr(shutdown_only):
     predictor = BatchPredictor.from_checkpoint(
         Checkpoint.from_dict({"factor": 2.0}),