Credit risk assessment is a critical function in the banking sector, directly influencing financial stability, asset quality, and regulatory compliance. Traditional credit evaluation models, largely based on historical financial data and rule-based systems, often fail to capture complex borrower behavior and dynamic market conditions. Predictive analytics, powered by machine learning and advanced statistical techniques, offers enhanced accuracy and adaptability in assessing credit risk. This stu