This paper researches a method to predict tunneling-induced ground subsidence with artificial neural network.Based on MATLAB system,a multi-layer back propagation neural network model was developed,in which the effects of the depth from surface to the tunnel axis,tunnel diameter,groundwater level,as well as the elastic modulus,shear strength,side pressure coefficient and unit weight of soil and the space between excavated wall and lining on the ground subsidence were considered.The developed prediction model is trained and tested with the data obtained from different tunnel projects in different countries.It shows that the predicted results are in well accordance with the field observations.