diff --git a/python/ray/air/predictor.py b/python/ray/air/predictor.py
index a4d76f97c..2d0d9854e 100644
--- a/python/ray/air/predictor.py
+++ b/python/ray/air/predictor.py
@@ -50,8 +50,9 @@ class Predictor(abc.ABC):
     To implement a new Predictor for your particular framework, you should subclass
     the base ``Predictor`` and implement the following two methods:
 
-        1. ``_predict_pandas``: Given a pandas.DataFrame input, return a
-           pandas.DataFrame containing predictions.
+        1. ``_predict_pandas`` or ``_predict_arrow``: Given a
+            pandas.DataFrame/pyarrow.Table input, return a
+            pandas.DataFrame/pyarrow.Table containing predictions.
         2. ``from_checkpoint``: Logic for creating a Predictor from an
            :ref:`AIR Checkpoint <air-checkpoint-ref>`.
     """
@@ -111,6 +112,24 @@ class Predictor(abc.ABC):
         """
         raise NotImplementedError
 
+    @DeveloperAPI
+    def _predict_arrow(self, data: "pyarrow.Table", **kwargs) -> "pyarrow.Table":
+        """Perform inference on an Arrow Table.
+
+        Predictors can implement this method instead of ``_predict_pandas``
+        for better performance when the input batch type is a Numpy array, dict of
+        numpy arrays, or an Arrow Table as conversion from these types are zero copy.
+
+        Args:
+            data: An Arrow Table to perform predictions on.
+            kwargs: Arguments specific to the predictor implementation.
+
+        Returns:
+            An Arrow Table containing the prediction result.
+        """
+
+        raise NotImplementedError
+
     def __reduce__(self):
         raise PredictorNotSerializableException(
             "Predictor instances are not serializable. Instead, you may want "