Target threatening level decision is a crucial method in planning air strike. For improving its accuracy, based on index system of threatening level, BP Neural Network has been used, and after trained and tested by training samples, the BP NN model is been built. The result shows that this model overcomes human factors, and improves the accuracy and adaptability of threatening evaluation, which can help staff officers make operation plans.