Abstract: A lot of experiments have shown that there is an obvious relation between surface qualities of specimen after laser shock-processing(LSP) and its fatigue life.Consequently,the LSP effects can be evaluated by surface qualities in LSP areas.In this paper,an artificial neural network(ANN) is utilized to study the surface qualities of specimen after LSP.Based on the data obtained in the experiment,an ANN is established.The trained ANN could acquire the relations between surface qualities and laser parmeters.From the verification of aluminium alloy 2024-T62,it is proved that the neural network can successfully predict the surface quality grades of specimen after LSP,and easily determine the laser parameters under different production conditions.The research and experimental results show that the ANN has not only the accuracy and good stability,but also the intelligent improving control ability during process.