Objective To study the method for improving forecasting accuracy of monitor color space conversion based on genetic algorithm to optimize the BP neural network. Methods The weights and threshold of the BP neural network were optimized mainly through the improvement of data normalization and the fitness function of genetic algorithm, to narrow down their distribution range, and then BP algorithm was solved exactly. This mode was then compared to the normal mode. Results After 20 times training of the optimized BP neural network prediction model, the average color difference in test blocks reached 2. 9353, and the minimal average color difference reached 1. 9467. Conclusion The results showed that the method can greatly reduce the possibility of falling into local minima of the BP neural network prediction model, with good non-linear fitting capability and higher prediction accuracy of color space conversion.