Based on the main experiment parameters of DyFe2 alloy preparation by reduction-diffusion process: reaction temperature, holding time, added quantity of Ca and particle size of Fe, the BP neural network was established and used to predicate the transformation efficiency of DyFe2 alloy. The neural network was simulated by 44 groups of experimental data and was tested. It has been proved that the neural network has good performance to predict the transformation efficiency of DyFe2 alloy. This design of neural network is able to shorten the time of experiment, reduce the experiment cost, and optimize the preparation processes.