At present, in the behavior prediction of relay protection equipment, the state transition model is used for state classification and probability prediction. The description of the influence of equipment aging and planned maintenance factors on the prediction model is not accurate enough, and it is thus difficult to accurately reflect the future behavior of the relay protection equipment. Based on the improved three-parameter Weibull distribution that characterizes equipment aging and maintenance, this paper uses the whale algorithm to further enhance the three-parameter Weibull distribution function, constructs a continuous Markov chain state transition model with a time-varying transition rate. In this model, planned maintenance nodes are used to characterize the service age regression of the protection equipment, the state observation node to simplify the calculation of the transition probability, and then an action behavior prediction algorithm that calculates the time-varying transition rate and planned maintenance can be proposed. The Weibull curve is calculated and fitted based on the case database, and the predicted actions are comprehensively analyzed through the simulated comparison experiments, which verifies the rationality of the state transition model and the prediction algorithm.