diff --git a/src/models/train.py b/src/models/train.py
index a2f7e50..9cd01be 100644
--- a/src/models/train.py
+++ b/src/models/train.py
@@ -13,14 +13,25 @@ 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
-mlflow.set_tracking_uri(os.getenv("MLFLOW_TRACKING_URI", "https://mlflow.sortifal.dev"))
+# Configure MLflow with authentication
+tracking_uri = os.getenv("MLFLOW_TRACKING_URI", "https://mlflow.sortifal.dev")
+username = os.getenv("MLFLOW_TRACKING_USERNAME")
+password = os.getenv("MLFLOW_TRACKING_PASSWORD")
 
-# Set MLflow credentials from environment variables
-if os.getenv("MLFLOW_TRACKING_USERNAME") and os.getenv("MLFLOW_TRACKING_PASSWORD"):
-    os.environ["MLFLOW_TRACKING_USERNAME"] = os.getenv("MLFLOW_TRACKING_USERNAME")
-    os.environ["MLFLOW_TRACKING_PASSWORD"] = os.getenv("MLFLOW_TRACKING_PASSWORD")
-    print("MLflow credentials configured from environment variables")
+# 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}")
+else:
+    mlflow.set_tracking_uri(tracking_uri)
+    print("MLflow configured without authentication")
 
 # Try to set experiment, but handle auth errors gracefully
 USE_MLFLOW = True