diff --git a/frigate/api/classification.py b/frigate/api/classification.py
index eee637585..48b26e355 100644
--- a/frigate/api/classification.py
+++ b/frigate/api/classification.py
@@ -112,9 +112,18 @@ def reclassify_face(request: Request, body: dict = None):
     context: EmbeddingsContext = request.app.embeddings
     response = context.reprocess_face(training_file)
 
+    if not isinstance(response, dict):
+        return JSONResponse(
+            status_code=500,
+            content={
+                "success": False,
+                "message": "Could not process request.",
+            },
+        )
+
     return JSONResponse(
+        status_code=200 if response.get("success", True) else 400,
         content=response,
-        status_code=200,
     )
 
 
diff --git a/frigate/data_processing/real_time/face.py b/frigate/data_processing/real_time/face.py
index 2c6b02103..db3cb22ed 100644
--- a/frigate/data_processing/real_time/face.py
+++ b/frigate/data_processing/real_time/face.py
@@ -423,7 +423,10 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
             res = self.recognizer.classify(img)
 
             if not res:
-                return
+                return {
+                    "message": "No face was recognized.",
+                    "success": False,
+                }
 
             sub_label, score = res
 
@@ -442,6 +445,13 @@ class FaceRealTimeProcessor(RealTimeProcessorApi):
                 )
                 shutil.move(current_file, new_file)
 
+            return {
+                "message": f"Successfully reprocessed face. Result: {sub_label} (score: {score:.2f})",
+                "success": True,
+                "face_name": sub_label,
+                "score": score,
+            }
+
     def expire_object(self, object_id: str, camera: str):
         if object_id in self.person_face_history:
             self.person_face_history.pop(object_id)