A compensation model based on neural network was put forward to solve the prediction uncertainty low precision problems of neural network model in color separation algorithm. The model synthesizes each channel difference of neural network predicting CMYK to L*a*b* polynomial function, and compensates for the CMYK values. Experimental results showed that the new model has improved accuracy of color separation algorithm after CMYK value compensation; separation accuracy of the model is higher than other commonly used models.