Abstract: Climate change and anthropogenic activities are profoundly affecting species distribution range and habitat suitability. In recent years, using models to predict potential suitable habitats for different species has become one of the research focuses in this field. The maximum entropy model (MaxEnt), a machine learning model based on the data of species distribution and environmental variables, has been widely used in predicting species habitats. First, we introduced the mechanism, establishment process, optimization method and assessment system of the MaxEnt model. Then, we reviewed the application of the model in potential habitat prediction of endangered species and invasive species, and the simulation of the potential distribution of species under future climate change. Fina-lly, we proposed current challenges and future development prospects of the MaxEnt model, aiming to strengthen its role in predicting the natural distribution of species, and provide technical references for biodiversity conservation and management.

Key words: species; MaxEnt model; habitat; suitability; biodiversity