Forecast of surrounding rock displacement is significant for tunnel engineering. The model of BP neural network Markov chain was adopted to the displacement forecast for tunnel surrounding rock. Through emulating the training samples, rolling forecast for the displacement time series was performed by BP neural network, and the relative error of measured and predicted values was acquired. Furthermore, the Markov chain was employed to correct the relative error, and  the forecast results were improved. The model was applied to the time-series forecast of the vault settlement of a real vehicular tunnel, and the result showed that the model is of high precision and reliability. It provides a new approach for the forecast of tunnel's  surrounding rock displacement.