Based on the industry data and enterprise data from tens of thousands of small and medium-sized enterprises, a deep learning and machine learning model of credit prediction is constructed through the division of data sets, processing, and integration of models. At first, with the help of two characteristic selection methods, several subsets separated from the dataset are analyzed based on convolutional neural network as coarse prediction. Then, combined with the tree model, the precise prediction is further made for the enterprise credit evaluation. Finally, the model fusion is carried out to obtain high-precision results. In the simulation experiment, this paper takes a data set of 14,366 small and medium-sized enterprise credit evaluations as the analysis samples to verify the results. The accuracy of the model is 97%, which is far more than 93% of single model with metadata set.