Aiming at the driving comfort problem of a sporty large-displacement motorcycle, an optimization scheme was proposed. Through the simulation analysis of the motorcycle on the C-level road, the pitch vibration and vertical vibration acceleration, which characterize the riding comfort of the motorcycle, were obtained, and the above two index peaks were used as the target response. Sensitivity analysis and approximate modeling of related parameters were carried out, and the radial basis function neural network approximate model was used for multi-objective optimization, based on the error analysis of the approximate model. The results show that after optimization, the actual vehicle verified that the pitch vibration acceleration peak was reduced by 17.21%, and the front and rear wheel vertical vibration acceleration peaks were reduced by 8.11% and 24.18%, respectively, which improved the ride comfort of the motorcycle and verified the effectiveness of the optimization scheme.