To deal with low accuracy of single BP neural network in the prediction of laboratory equipment demand, a prediction model based on grey relation analysis and BP neural network is proposed. The correlation degrees between influencing factors were first calculated using grey relation analysis method. Three major factors with higher correlation degrees were chosen as training samples for the BP neural network and a threelayered BP network prediction model was established. The real laboratory equipment demand of an experiment was taken as an example to test the algorithm. And a comparative analysis of the prediction accuracy of the grey BP network model and the single BP network model was done. The result shows that the grey BP network model reduces the topology of BP network from 6101 to 361. Its maximum relative error is -1.36%, while the one of the single BP network model is -4.18%. The prediction accuracy of the grey BP network model is higher and its structure is also simpler.