To bring more reasonable scheduling of taxi resources, this study proposes an intelligent taxi forecasting system based on machine learning. Firstly, the GPS data set of Porto taxi is preprocessed, and a part of the training sets are taken as the research object. Then the echo state network algorithm is used to predict the travel destination of the taxi under the premise of predicting the travel destination. Finally, the taxi arrival time is predicted by using random forest algorithm in the same circumstances. Experiments show that the system can predict the actual taxi destination of the part of the journey and the time required for the journey, thus achieved the purpose of reducing the waste of taxi resources based on the current Porto taxi GPS data set.