In this paper, chaos prediction of motor system is realized based on the next generation reservoir computing, and unknown variable data can be predicted based on existing data. Compared with the traditional reservoir computing, the next generation reservoir computing uses direct connection of data itself and requires smaller training data sets. And the next generation reservoir computing avoids the complex parameter optimization calculation of traditional reserve pool network through high-dimensional conversion, which greatly improves the computing speed. This research result provides a new research idea for chaotic prediction of motor systems.