Aiming at the difficulty of toric spectacle lens machining, parameters of slow tool servo were optimized. Based on Response Surface Methodology(RSM), influence of tool nose radius, feed rate, depth of cut, spindle speed and discretization angle on surface quality was discussed. Using surface roughness as the response, the multiple regression model was established . Desirability function approach was used to solve the multiple regression model, and the optimum parameters (i.e. tool nose radius of 0.89 mm, feed rate of 5 μm/r, depth of cut of 5 μm, spindle speed of 200.32 r/min and discretization angle of 5.64°) were determined. Through the model, the interaction between various factors and their influences on surface quality were analyzed. Tool nose radius exerted the maximum effect on the surface roughness, feed rate and depth of cut followed. The verification test indicated that the roughness of complex surface turning could be predicted by the RSM model.