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The last decade witnessed a significant increase in net private capital inflows in China. Some of them are short-term capital flows, which are typically considered to be highly volatile. For effectively forecasting the short-term capital flows, a three-layered neural feedforward network was employed in this paper. In light of the weakness of the conventional Back-Propagation algorithm, the Levenberg-Marquardt algorithm was used to train the neural network. The simulation results indicate that the predictive model can be used to carry out the prediction of short-term capital flow.