The present invention provides a novel prognostic and health management method for natural aging systems. This prognostic and health management method can detect anomalies in a system in advance, and can determine whether the detected anomalies are due to natural aging or other aging processes. In this prognostic method, a moving window method for improving the performance of the conventional data-driven prognostic methods is described. This prognostic and health management method combines with the detections by the data-driven prognostic method based on the conventional training and moving window methods to determine whether the detected anomalies are due to natural aging or other aging processes and in so doing can reduce the number of false alarms; reduce cost of a system by decreasing the unnecessary maintenance, downtime, and inventory; can extend the life of systems; and can assist in the design and qualification of future systems to improve their reliability.