diff --git a/apps/ml-service/main.py b/apps/ml-service/main.py
index ad45bcf..ca79390 100644
--- a/apps/ml-service/main.py
+++ b/apps/ml-service/main.py
@@ -44,6 +44,9 @@ async def predict(file: UploadFile = File(...)) -> PredictionResponse:
     except ImageDecodeError as exc:
         raise HTTPException(status_code=400, detail=str(exc)) from exc
     except Exception as exc:
+        import logging
+
+        logging.exception("Prediction failed")
         raise HTTPException(status_code=500, detail="Prediction failed") from exc
 
     return PredictionResponse(
diff --git a/apps/ml-service/model.py b/apps/ml-service/model.py
index 26dd96a..8d238ad 100644
--- a/apps/ml-service/model.py
+++ b/apps/ml-service/model.py
@@ -1,4 +1,5 @@
 from io import BytesIO
+import logging
 import os
 from pathlib import Path
 
@@ -7,7 +8,7 @@ from PIL import Image, UnidentifiedImageError
 import tensorflow as tf
 
 
-LABELS = ["Bercak Daun", "Hawar Daun", "Karat Daun", "Daun Sehat"]
+LABELS = ["Bercak Daun", "Daun Sehat", "Karat Daun", "Hawar Daun"]
 SERVICE_NAME = "zeavis-ml-service"
 SERVICE_VERSION = "0.1.0"
 
@@ -40,6 +41,7 @@ class ModelService:
         except Exception as exc:
             self.model = None
             self.load_error = str(exc)
+            logging.exception("Failed to load ML model from %s", self.model_path)
 
     def preprocess(self, image_bytes: bytes) -> np.ndarray:
         try:
diff --git a/apps/ml-service/test_model.py b/apps/ml-service/test_model.py
new file mode 100644
index 0000000..5c7de33
--- /dev/null
+++ b/apps/ml-service/test_model.py
@@ -0,0 +1,15 @@
+import unittest
+
+from model import LABELS
+
+
+class ModelServiceTests(unittest.TestCase):
+    def test_labels_match_training_class_order_with_display_names(self) -> None:
+        self.assertEqual(
+            LABELS,
+            ["Bercak Daun", "Daun Sehat", "Karat Daun", "Hawar Daun"],
+        )
+
+
+if __name__ == "__main__":
+    unittest.main()