Abstract: A more direct analysis method based on neural network is proposed. Taking the machining centers as the research objects, the main performance parameters such as the spindle power, maximum rotating speed, positioning accuracy, repeat positioning accuracy, and fast moving speed of domestic and foreign products are collected through big data. Using the neural network model under Python framework to explore the weight of the influence of each parameter on the quality and performance of the machine tools. At the same time, a classification and evaluation method of machine tools' quality is proposed by using the classification and prediction functions of neural networks, thereby solving the problem that it is difficult to reasonably quantify the quality of machine tools. The analysis results show that this method can analyze the key factors that affect the quality of machine tools, and can also perform a preliminary classification of machine tool quality, which has guiding significance for the evaluation of machine tool performance.