Bleeding risk stratification tools are essential for optimizing ischemic protection while minimizing bleeding complications, particularly in patients undergoing percutaneous coronary intervention (PCI) or dual antiplatelet therapy (DAPT). A structured search of PubMed, Scopus, and Web of Science was conducted for studies published from January 2005 to December 2024. This review evaluates traditional and novel bleeding risk models in MI management. Established tools like CRUSADE, ACUITY-HORIZONS, ACTION, and PRECISE-DAPT aid in predicting in-hospital and early post-discharge bleeding but have limitations in long-term risk assessment and adapting to modern PCI techniques. Emerging models - SWEDEHEART, ARC-HBR, BLEED-MI, CREDO-KYOTO, and BleeMACS - offer enhanced risk stratification by incorporating broader clinical variables and long-term bleeding predictors, improving their applicability to contemporary MI management. Despite advancements, current models exhibit moderate predictive accuracy (c-statistics 0.70-0.80) and rely on static baseline factors, limiting real-time applicability. They also fail to integrate ischemic risk assessment, creating challenges in balancing thrombotic and bleeding risks. Future research should focus on AI-driven dynamic risk models, broader validation across diverse populations, and integrating bleeding and ischemic risk stratification into a unified framework. Embedding these tools into electronic health records (EHRs) will enhance clinical decision-making and improve patient outcomes.