The sea surface wind speed is an important parameter of marine environment and satellite microwave radiometer is an important tool to monitor this parameter. In this paper, a model for retrieving the sea surface wind speed is developed using the artificial neural network (ANN), through the data sets generated between the microwave radiometer SSM/I brightness temperatures and the insitu buoy measurements. By comparing the retrieval results of different models, it is concluded that the result of the sevenchannel SANN retrieval model is closer to the buoy measured wind speed with the root mean square error (RMSE) of 1.40m/s. Therefore, this model is chosen to retrieve the global monthlyaverage wind speed, and the retrieval results are compared with the NOAA products. The results show that, both are very close in the overall and latitudeaverage distribution with the RMSE of 1.03 m/s. It can be seen that the algorithm for the sea surface wind speed retrieval is feasible.