Personalized prevention based on individual health data is vital in modern healthcare. We analyzed four years of checkup data from 96,093 individuals (20–74 years) to map transitions from healthy states to mibyo (pre-disease) and disease onset. Using dimensionality reduction and clustering, we identified 43 male and 33 female health status clusters, revealing distinct transition trajectories that inform targeted preventive strategies.