Abstract The high-pressure rotor speeds, low-pressure rotor speeds, and exhaust temperature of the aircraft engine are the key parameters reflecting the performance of aircraft engines. To realize the trend monitoring during the flight test and the processing of data outliers in flight data recorder, the time series analysis and modeling method is used to establish a suitable ARMA model through data processing, series property analysis, model identification, order determination, modeling, model diagnosis and other steps. Fit the real flight test data of an engine. The results show that the prediction interval within 3 steps of the ARMA model has high accuracy, and has good engineering practicability in real-time flight monitoring and data processing.