diff --git a/src/models/train.py b/src/models/train.py
index 9cd01be..0cd2331 100644
--- a/src/models/train.py
+++ b/src/models/train.py
@@ -13,25 +13,15 @@ from sklearn.ensemble import RandomForestClassifier
 from sklearn.metrics import accuracy_score, precision_score, recall_score, f1_score, roc_auc_score
 import pandas as pd
 
-# Configure MLflow with authentication
+# Configure MLflow
+# MLflow will automatically use MLFLOW_TRACKING_USERNAME and MLFLOW_TRACKING_PASSWORD env vars
 tracking_uri = os.getenv("MLFLOW_TRACKING_URI", "https://mlflow.sortifal.dev")
-username = os.getenv("MLFLOW_TRACKING_USERNAME")
-password = os.getenv("MLFLOW_TRACKING_PASSWORD")
+mlflow.set_tracking_uri(tracking_uri)
 
-# Build authenticated URI if credentials are provided
-if username and password:
-    # Extract protocol and host from URI
-    if tracking_uri.startswith("https://"):
-        auth_uri = f"https://{username}:{password}@{tracking_uri[8:]}"
-    elif tracking_uri.startswith("http://"):
-        auth_uri = f"http://{username}:{password}@{tracking_uri[7:]}"
-    else:
-        auth_uri = tracking_uri
-    mlflow.set_tracking_uri(auth_uri)
-    print(f"MLflow credentials configured for {tracking_uri}")
+if os.getenv("MLFLOW_TRACKING_USERNAME") and os.getenv("MLFLOW_TRACKING_PASSWORD"):
+    print(f"MLflow configured with authentication for {tracking_uri}")
 else:
-    mlflow.set_tracking_uri(tracking_uri)
-    print("MLflow configured without authentication")
+    print(f"MLflow configured without authentication for {tracking_uri}")
 
 # Try to set experiment, but handle auth errors gracefully
 USE_MLFLOW = True