The work aims to study the method of optimizing BP neural network based on simulated annealing algorithm to predict the accuracy of color space conversion in inkjet printer. The weight and threshold of BP neural network were optimized by data normalization and simulated annealing algorithm to obtain the global optimal solution, and then the BP neural network was used to predict the color difference. BP neural network prediction model optimized with simulated annealing algorithm was tested for 15 times to get the average color difference of color lumps. Such color difference reached 2.3067, and the minimum average color difference reached 0.7892. The results show that the proposed method has a high accuracy in optimizing the BP neural network, and has better nonlinear fitting ability and higher prediction accuracy for the color space conversion of inkjet printer.