In laboratories and clinics, the ancient question of why some people age faster than others has long resisted a clean answer — until now. Researchers analyzing blood proteins from nearly 60,000 individuals have built a machine-learning framework capable of mapping the aging rate of more than 40 distinct cell types from a single blood draw, revealing that biological decay is neither uniform nor inevitable in its trajectory. The system predicts diseases like Alzheimer's, ALS, lung cancer, and diabetes up to 15 years before diagnosis, outperforming even the most established genetic risk markers.