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The predicting unstart of hypersonic inlet consists of calculating positions of pressure sensors and establishing classification of inlet start/unstart, the feature selection algorithm and the classification algorithm was taken to solve this two problems, the common algorithm(SVMRFE) is time intensive on computation. A 2D hypersonic inlet / isolator model were simulated to generate wall static pressures data set. Hybrid feature selection algorithm based on SVMRFE algorithm and Relief algorithm were used to select optimal pressure points, which were called as Relief-Corre algorithm, Relief-SVMRFE algorithm , Relief-PSO-SVMRFE algorithm. The support vector machine (SVM) algorithm was used to train the classification plane. Finally, the performance of Relief-SVMRFE algorithm is proved best, since it’s operation efficiency is three times higher than SVMRFE and it has higher accuracy than other algorithms based on Relief. The hyperplane with strong robust performance and generalization performance conforms to the actual physical law, so the result shows that the criterion is valid.