You are working as a data scientist at a financial services company tasked with developing a credit risk prediction model. After experimenting with several models, including logistic regression, decision trees, and support vector machines, you find that none of the models individually achieves the desired level of accuracy and robustness. Your goal is to improve overall model performance by combining these models in a way that leverages their strengths while minimizing their weaknesses. Given the scenario, which of the following approaches is the MOST LIKELY to improve the model’s performance?