diff --git a/samples/snippets/classification_boosted_tree_model_test.py b/samples/snippets/classification_boosted_tree_model_test.py
index fbc9369dde..707ce16279 100644
--- a/samples/snippets/classification_boosted_tree_model_test.py
+++ b/samples/snippets/classification_boosted_tree_model_test.py
@@ -14,7 +14,7 @@
 
 
 def test_boosted_tree_model(random_model_id: str) -> None:
-    # your_model_id = random_model_id
+    your_model_id = random_model_id
     # [START bigquery_dataframes_bqml_boosted_tree_prepare]
     import bigframes.pandas as bpd
 
@@ -39,4 +39,28 @@ def test_boosted_tree_model(random_model_id: str) -> None:
     )
     del input_data["functional_weight"]
     # [END bigquery_dataframes_bqml_boosted_tree_prepare]
+    # [START bigquery_dataframes_bqml_boosted_tree_create]
+    from bigframes.ml import ensemble
+
+    # input_data is defined in an earlier step.
+    training_data = input_data[input_data["dataframe"] == "training"]
+    X = training_data.drop(columns=["income_bracket", "dataframe"])
+    y = training_data["income_bracket"]
+
+    # create and train the model
+    census_model = ensemble.XGBClassifier(
+        n_estimators=1,
+        booster="gbtree",
+        tree_method="hist",
+        max_iterations=1,  # For a more accurate model, try 50 iterations.
+        subsample=0.85,
+    )
+    census_model.fit(X, y)
+
+    census_model.to_gbq(
+        your_model_id,  # For example: "your-project.census.census_model"
+        replace=True,
+    )
+    # [END bigquery_dataframes_bqml_boosted_tree_create]
     assert input_data is not None
+    assert census_model is not None