This study explores the significant impact of Management Information Systems (MIS) on credit risk assessment in commercial banks, examining how these systems enhance decision-making accuracy, operational efficiency, and proactive risk management. By synthesizing findings from 50 peer-reviewed studies, the research reveals that banks using MIS experience a 20-30% reduction in non-performing loans and a 40-50% increase in loan processing speed due to automation and real-time data analysis. The integration of advanced technologies such as artificial intelligence (AI) and predictive analytics further improves credit risk forecasting accuracy by 15-20%, enabling banks to implement proactive risk mitigation strategies that reduce borrower defaults by up to 25%. However, the study also highlights significant challenges, particularly for smaller banks, which face high implementation costs and difficulties integrating MIS with legacy systems. Despite these challenges, the role of MIS in ensuring regulatory compliance, particularly under Basel III, and reducing overall credit exposure by 15-20% underscores its critical importance in modern credit risk management. The findings suggest that while MIS is essential for maintaining financial stability and competitiveness, scalable and cost-effective solutions are necessary for broader adoption across the banking industry.