In order to solve the misjudgment and timeconsuming problem in manual identification of aeroengine working condition, and to improve the accuracy of the recognition, an intelligent recognition method based on principal component analysis（PCA）and a random forest（RF）is proposed. Firstly, PCA is used to reduce the dimensionality of the original flight data preprocessed, and the processed data on the basis of aeroengine working condition are grouped, and then RF are constructed. Secondly, the recognition effect of several classification methods is made in comparison with each other. At last, the method is used to recognize the working condition of one sort. The experiment results indicate that the recognition accuracy is 97.89% by this method. And this method is able to recognize the aeroengine working condition fast and accurately, and simultaneously is able to apply to the research related to the aeroengine working condition.