Abstract: As an important research method in biogeography and macroecology, Species Distribution Models(SDMs) play an important role in the fields of life science and environmental science. Among many species distribution models, Maximum Entropy model(MaxEnt) stands out among them because of its advantages such as its low data requirements, high predicted accuracy, easy-to-use operational steps and so on. By reading the related literatures and works about Maximum Entropy model currently published, we tried to describe its development process and optimization from three perspectives: the development of the Maximum Entropy model at home and abroad, its applications in different climatic backgrounds and regional scales. On the basis of comprehensive analysis, we adopt an idea of expanding the prediction range and the sample size of prediction data to build a model to solve the problem of too little data and the investigation of biodiversity in blank areas.