In the intelligent traffic system, accurately grasp the intrinsic changes in the traffic flow law, and timely scientific prediction of the future traffic flow for a number of moments, will have a very important significance to traffic guidance work, traffic management work, traffic planning work, etc. In this paper, we propose a short-time traffic flow prediction model based on random forest regression(RFR) algorithm, and improve the performance of the model by adjusting the hyperparameters of the model. The performance of the random forest model was also compared with the support vector regression (SVR) model and the decision tree regression(DTR) model, and the RFR model ultimately yielded the best predictions.