diff --git a/optimum/exporters/onnx/model_configs.py b/optimum/exporters/onnx/model_configs.py
index 0e37259f7b..9bbfacf235 100644
--- a/optimum/exporters/onnx/model_configs.py
+++ b/optimum/exporters/onnx/model_configs.py
@@ -1342,9 +1342,15 @@ class WhisperOnnxConfig(AudioToTextOnnxConfig):
 
     @property
     def inputs(self) -> Dict[str, Dict[int, str]]:
-        common_inputs = super().inputs
-        if self._behavior is ConfigBehavior.DECODER and self.use_past_in_inputs is False:
-            common_inputs["encoder_outputs"][1] = f"{common_inputs['encoder_outputs'][1]} / 2"
+        if self.task == "audio-classification":
+            common_inputs = {"input_features": {0: "batch_size"}}
+        else:
+            common_inputs = super().inputs
+            if self._behavior is not ConfigBehavior.DECODER:
+                common_inputs["input_features"] = {0: "batch_size"}  # Remove unnecessary dynamic axis.
+
+            if self._behavior is ConfigBehavior.DECODER and self.use_past_in_inputs is False:
+                common_inputs["encoder_outputs"][1] = f"{common_inputs['encoder_outputs'][1]} / 2"
         return common_inputs
 
     @property
diff --git a/optimum/exporters/tasks.py b/optimum/exporters/tasks.py
index 2f5794eecd..57ee54c2c7 100644
--- a/optimum/exporters/tasks.py
+++ b/optimum/exporters/tasks.py
@@ -1062,6 +1062,7 @@ class TasksManager:
         "whisper": supported_tasks_mapping(
             "feature-extraction",
             "feature-extraction-with-past",
+            "audio-classification",
             "automatic-speech-recognition",
             "automatic-speech-recognition-with-past",
             onnx="WhisperOnnxConfig",
diff --git a/optimum/onnxruntime/modeling_ort.py b/optimum/onnxruntime/modeling_ort.py
index 413acbc233..4ebf318aa7 100644
--- a/optimum/onnxruntime/modeling_ort.py
+++ b/optimum/onnxruntime/modeling_ort.py
@@ -1832,6 +1832,29 @@ class ORTModelForAudioClassification(ORTModel):
 
     auto_model_class = AutoModelForAudioClassification
 
+    def __init__(
+        self,
+        model: ort.InferenceSession,
+        config: "PretrainedConfig",
+        use_io_binding: Optional[bool] = None,
+        model_save_dir: Optional[Union[str, Path, TemporaryDirectory]] = None,
+        preprocessors: Optional[List] = None,
+        **kwargs,
+    ):
+        super().__init__(
+            model=model,
+            config=config,
+            use_io_binding=use_io_binding,
+            model_save_dir=model_save_dir,
+            preprocessors=preprocessors,
+            **kwargs,
+        )
+
+        if config.model_type == "whisper":
+            self.input_name = "input_features"
+        else:
+            self.input_name = "input_values"
+
     @add_start_docstrings_to_model_forward(
         ONNX_AUDIO_INPUTS_DOCSTRING.format("batch_size, sequence_length")
         + AUDIO_CLASSIFICATION_EXAMPLE.format(
@@ -1846,6 +1869,9 @@ def forward(
         attenton_mask: Optional[torch.Tensor] = None,
         **kwargs,
     ):
+        if input_values is None:
+            # Whisper uses input_features and not input_values.
+            input_values = kwargs["input_features"]
         use_torch = isinstance(input_values, torch.Tensor)
         self.raise_on_numpy_input_io_binding(use_torch)
         if self.device.type == "cuda" and self.use_io_binding:
@@ -1864,11 +1890,11 @@ def forward(
             if use_torch:
                 # converts pytorch inputs into numpy inputs for onnx
                 onnx_inputs = {
-                    "input_values": input_values.cpu().detach().numpy(),
+                    self.input_name: input_values.cpu().detach().numpy(),
                 }
             else:
                 onnx_inputs = {
-                    "input_values": input_values,
+                    self.input_name: input_values,
                 }
 
             # run inference
diff --git a/tests/onnxruntime/test_modeling.py b/tests/onnxruntime/test_modeling.py
index b9f7cdcd4d..6615a634df 100644
--- a/tests/onnxruntime/test_modeling.py
+++ b/tests/onnxruntime/test_modeling.py
@@ -3127,6 +3127,7 @@ class ORTModelForAudioClassificationIntegrationTest(ORTModelTestMixin):
         "wavlm",
         "wav2vec2",
         "wav2vec2-conformer",
+        "whisper",
     ]
 
     FULL_GRID = {"model_arch": SUPPORTED_ARCHITECTURES}