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There are hundreds of flight parameters and a large number of flight data during aircraft flight, but these data have not been fully and effectively utilized at present, and the maintenance of aircraft is still in the phase of regular maintenance and post-repair. With the continuous development of aviation technology, it is more and more necessary to make use of flight data to predict faults, and to change the maintenance mode of civil aircraft to the development of maintenance according to the situation. First, the fault prediction technology of civil aircraft based on QAR data is described. Secondly, two fault prediction methods for civil aircraft’s quick access recorder (QAR) data are introduced, including the performance prediction method based on curve fitting and the performance trend prediction based on time series. Again, the realization of fault prediction system based on flight data is described in detail. By predicting the change trend of key parameters, the fault can be detected in advance to make a reasonable maintenance plan and ensure flight safety. Finally, the proposed method is used to predict the key parameters of the air conditioning and lubricating system of Boeing aircraft, and the prediction results verify the effectiveness of the method.