The invention discloses an aero-engine 
remaining life prediction method based on multi-stage 
information fusion. The method comprises the steps that multi-source monitoring parameter denoising 
processing and 
feature extraction are conducted; stable analysis is conducted on multi-source monitoring time sequences, sudden 
change points of all parameter monitoring time sequences are calculated and parameter degeneration proportions at the positions of the sudden 
change points are calculated; multi-stage division is conducted on multi-source parameters, a regression fusion model is established, sample training is conducted by using historical 
monitoring data and parameters, in 
multiple stages, of the fusion model are obtained; according to 
monitoring data in a 
training set, the multi-source monitoring parameters are fused and a 
health indicator HI is obtained; by using the 
Kalman filtering algorithm, best fit is conducted on an engine in the whole process that the performance fails from being complete, and the error of a prediction model is minimized; according to real-time 
monitoring data in a 
test set, the multi-source monitoring parameters are fused and a 
health indicator HI is obtained; time-varying parameters of the prediction model are estimated in real time by using the 
Kalman filtering algorithm; the prediction model is determined, the time mechanism is introduced and the failure time of the engine is estimated in real time.