Abstract: To predict the tourism demand of Hainan province, the number of tourist was used to determine the tourism demand, the related data were collected, and the effects of the tourism resources, the environment, transportation, cost and service quality factors on the tourism demand were analyzed, and a multiple linear regression model was established. The GM (1, 1) model was performed to obtain the predict value, and the neural network model was used to predict the number of tourist each year of Hainan province. When the effects of season were taken into account, the SARIMA (3, 1, 2) (1, 1, 1)₁₂ model was established for predicting. The results indicated that the predict number was keeping with the actual number.