Abstract: Solar Proton Events （SPE） are one kind of the major, severe space environmental events that induces errors even failure of the satellites on the orbit. In this paper, a model of SPE forecasting employing artificial neural network technology by Space Environment Prediction Center （SEPC） is introduced. The strength of solar event is related with releused from the solar burst. The size of area of the sunspot indicates the maximum strength of local magnetic field. The Mclntosh classification of the sunspot indicates the structure of the root area of the magnetic rope from the sunspot regions. The joint applying of the Mclntosh classification and the magnetic type enable us to describe the structure of the sunspot. In this paper, 10.7cm radio and X-ray fluxes were used, and the Artificial Neural Network （ANN） is employed. The digitized morphology data are then arranged and "feed" into the neural network. Through training the model based on ANN algorithm a forecast model was constructed. With it, the forecast of SPE 1-3 days ahead can be made. Statistics shows that the accuracy of our forecast is about 80%.