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Parameters of phase space reconstruction are very important in network traffic prediction which is solved separately traditionally. In order to improve the prediction accuracy of network traffic, a novel network traffic prediction model (PSO-BPNN) is proposed in this paper based on particle swarm optimization algorithm and BP neural network. Firstly, BP neural network is taken as perdition algorithm, and the optimal delay time (τ) and embedding dimension (m) are obtained by particle swarm optimization and the network traffic series are reconstructed, finally, network traffic prediction models are established based on reconstruction the network traffic series, and simulation experiments are carried out to test the performance of network traffic prediction model. The results show that PSO-BPNN has improved the prediction accuracy of network traffic. 