diff --git a/requirements.txt b/requirements.txt
index cbf30d9..7895d3b 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -4,3 +4,4 @@ seaborn
 matplotlib
 joblib
 numpy
+xgboost
diff --git a/src/model.py b/src/model.py
index a0c986e..b5967b4 100644
--- a/src/model.py
+++ b/src/model.py
@@ -13,6 +13,7 @@
 from sklearn.metrics import precision_recall_curve
 from sklearn.metrics import roc_curve
 from sklearn.metrics import roc_auc_score
+from xgboost import XGBClassifier
 import matplotlib.pyplot as plt
 
 
@@ -29,20 +30,8 @@ def train(data, num_estimators, isDataFrame=False):
         X, y, test_size=0.3, random_state=0
     )
 
-    pipe = Pipeline(
-        [
-            ("scaler", StandardScaler()),
-            (
-                "RFC",
-                RandomForestClassifier(
-                    criterion="gini",
-                    max_depth=10,
-                    max_features="auto",
-                    n_estimators=num_estimators,
-                ),
-            ),
-        ]
-    )
+    pipe = Pipeline([('scaler', StandardScaler()), ('XGB', XGBClassifier())])
+
 
     training_logs = pipe.fit(X_train, y_train)