Abstract: We combine the learning vector quantization （ＬＶＱ） and GA-BP neural network to predict gas emission in the view of the characteristics of varied, nonlinear and complex gas emission in coal mine．The algorithm classified and selected the main influence factors, and used genetic algorithm to optimize the weight and threshold of BP neural network to construct the prediction model of mine gas emission quantity. LVQ-GA-BP prediction model established by related data is compared and analyzed with BP neural network, the result shows that the average relative error of this method is 0.025 51 and is lower than that of the BP neural network, and the method improves the prediction accuracy.