Understanding the dynamics of Leaf Area Index （LAI） in tropical evergreen forests is crucial for assessing ecosystem health and carbon dynamics. In this paper， a method is proposed for decomposing LAI into leaf age cohorts in tropical evergreen broadleaf forests across Amazon Basin. The method simplifies the canopy into three major leaf age stages （i.e.， young， mature， and old leaves）. The method integrates leaf-level photosynthetic biochemistry models with remote sensing climate data to simulate carbon assimilation across these leaf age stages. Then， utilizing a novel neighbor-based approach and the linear least squares solver with bounds or linear constraints （Lsqlin） to derive the values of three LAI cohorts. Validation against ground-based phenology camera data shows good agreement in seasonal dynamics of LAI cohorts （LAI_young： R² = 0.32； LAI_mature： R² = 0.61 and LAI_old： R² = 0.49）， indicating the method's ability to capture seasonal variations accurately. Spatial patterns of LAI cohorts closely correspond to climatic phenology variables across the Amazon Basin. This approach enhances our understanding of LAI dynamics in tropical forests， providing valuable insights for ecosystem management and carbon cycle modeling in the Amazon Basin.