Sensory pleasantness evaluation of eighteen vehicle exhaust noises were obtained by paired comparison jury test. Loudness, sharpness, roughness, fluctuation strength and kurtosis were selected for objectively characterizing the sound quality of exhaust noise. The sound quality prediction model of vehicle exhaust noise was established based on back-propagation neural network. Sensory pleasantness of exhaust noise samples were obtained through the prediction model and the results were compared with that obtained through multiple linear regression prediction model. The result showed that the prediction values were close to the measured values, the neural network model was more effective than multiple linear regression model in prediction of individual exhaust noise. The neural network prediction model represented the nonlinear relation between sensory pleasantness and objective parameters exactly and could be used for predicting the sound quality of vehicle exhaust noise.