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The prediction of lithium battery charge status (SOC) is one of the most critical technologies in lithium battery management system of electric vehicles. In order to realize the high-precision prediction of SOC, a lithium battery SOC prediction method based on Cuckoo search algorithm (CS) optimization is proposed, the core of which is to optimize the initial weight and threshold of BP neural network, so as to overcome the disadvantages of local optimality and reduce the algorithm's dependence on the initial value. The MATLAB simulation results show that the average square root error value of CS-BP neural network algorithm is 0.0106 lower than that of BP algorithm, and the CS-BP algorithm has better prediction accuracy and generalization performance.