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Among many automotive batteries, lithium batteries have become an excellent choice for power batteries for electric vehicles due to their stable performance, long life, and strong endurance. In order to efficiently manage the lithium battery, prevent overcharging and overdischarge, and ensure the safety and performance of the lithium battery, it is necessary to accurately predict the state of charge (SOC) of the lithium battery. The experiment is based on the actual data of the lithium battery charging process, using Pyhton language programming to establish a multiple linear regression model, through the model to predict the accurate SOC value of the lithium battery from the beginning of charging to the end of the charging process. The research results show that the change process of SOC of lithium battery has a certain linear law. The error of multivariate linear regression model to predict SOC value can be controlled to be small, the coefficient of determination is higher than 99%, and has good prediction effect and certain the versatility. In addition, the multiple linear regression model has fewer parameters, is simple in structure, easy to implement, and is more easily popularized in practical applications.