The choice between CatBoost and XGBoost depends on the specific task, dataset, and requirements. Both CatBoost and XGBoost are powerful gradient boosting frameworks with their own strengths. CatBoost excels in handling categorical features and missing values, while XGBoost offers extensive hyperparameter tuning options and is widely used in machine learning competitions. It is recommended to evaluate both frameworks on your specific use case to determine which one suits your needs better.