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In order to keep the armored vehicles safe and reliable, it is very important to improve the ability of predicting the state of health of lead-acid batteries. In this paper, a method of SOH prediction for armored vehicle batteries based on GA-ANFIS is proposed, which combines genetic algorithm with adaptiveSnetwork-based fuzzy inference system. The overall process and training process of the method are emphatically analyzed. Aiming at the working environment of armored vehicles, elevation and temperature are introduced as the input of the model on the basis of discharge depth and output energy. The experimental results in Matlab show that the error of GA-ANFIS is 47.6% less than that of ANFIS, and that of four-input GA-ANFIS is 51.2% less than that of two-input GA-ANFIS.