diff --git a/frigate/api/classification.py b/frigate/api/classification.py
index 6405516e0..9808e0dc0 100644
--- a/frigate/api/classification.py
+++ b/frigate/api/classification.py
@@ -40,10 +40,10 @@ def get_faces():
 @router.post("/faces/{name}")
 async def register_face(request: Request, name: str, file: UploadFile):
     context: EmbeddingsContext = request.app.embeddings
-    context.register_face(name, await file.read())
+    result = context.register_face(name, await file.read())
     return JSONResponse(
-        status_code=200,
-        content={"success": True, "message": "Successfully registered face."},
+        status_code=200 if result.get("success", True) else 400,
+        content=result,
     )
 
 
diff --git a/frigate/embeddings/__init__.py b/frigate/embeddings/__init__.py
index 43da686ce..05c49013e 100644
--- a/frigate/embeddings/__init__.py
+++ b/frigate/embeddings/__init__.py
@@ -192,8 +192,8 @@ class EmbeddingsContext:
 
         return results
 
-    def register_face(self, face_name: str, image_data: bytes) -> None:
-        self.requestor.send_data(
+    def register_face(self, face_name: str, image_data: bytes) -> dict[str, any]:
+        return self.requestor.send_data(
             EmbeddingsRequestEnum.register_face.value,
             {
                 "face_name": face_name,
diff --git a/frigate/embeddings/maintainer.py b/frigate/embeddings/maintainer.py
index 6aa503624..e7c2605e4 100644
--- a/frigate/embeddings/maintainer.py
+++ b/frigate/embeddings/maintainer.py
@@ -144,7 +144,10 @@ class EmbeddingMaintainer(threading.Thread):
                     )
                 elif topic == EmbeddingsRequestEnum.register_face.value:
                     if not self.face_recognition_enabled:
-                        return False
+                        return {
+                            "message": "Face recognition is not enabled.",
+                            "success": False,
+                        }
 
                     rand_id = "".join(
                         random.choices(string.ascii_lowercase + string.digits, k=6)
@@ -164,7 +167,10 @@ class EmbeddingMaintainer(threading.Thread):
                         face_box = self._detect_face(img)
 
                         if not face_box:
-                            return False
+                            return {
+                                "message": "No face was detected.",
+                                "success": False,
+                            }
 
                         face = img[face_box[1] : face_box[3], face_box[0] : face_box[2]]
                         ret, thumbnail = cv2.imencode(
@@ -181,7 +187,10 @@ class EmbeddingMaintainer(threading.Thread):
                         output.write(thumbnail.tobytes())
 
                 self.face_classifier.clear_classifier()
-                return True
+                return {
+                    "message": "Successfully registered face.",
+                    "success": True,
+                }
             except Exception as e:
                 logger.error(f"Unable to handle embeddings request {e}")