In view of the lack of reliability analysis methods, small fault samples and relatively conservative maintenance strategies of aircraft integral drive generators, a reliability analysis method based on Bayesian and Markov chain fusion driven by historical fault data was proposed. Firstly, the Monte Carlo method was used to preprocess the fault data to increase the sample space, and the prior distribution of the aircraft overall drive generator was solved by the maximum information entropy method. Secondly, the Markov chain method was used to solve the complex posterior distribution. Finally, the maintenance suggestions of the aircraft IDG ( integral drive generator) were given based on the reliability. The cumulative failure function parameter estimation errors of IDG calculated by numerical simulation software are 0. 121 3 and 0. 001 3 respectively, with small errors. The simulation results show that the proposed reliability analysis method is suitable for aircraft IDG reliability analysis in small sample space, and maintenance suggestions were given according to the results.