Intelligent models including Grey Model (GM(1,1)), BP neural network, and the combination of the two models Grey Neural Network Model (GNNM(1,1)) were employed in the prediction of anchorage foundation deformation. Monitored soil pressure of the north anchorage foundation of Runyang Bridge was taken to dynamically predict the deformation by these three models. The predictions were further compared with the measured soil pressures. The comparison showed that there is a relative error of 1.11% ，0.77%and 0.43% respectively of each model’s prediction result. Compared with the other two models, the prediction of GNNM(1,1) was closer to the measured soil pressure, and it can be applied in actual prediction process as it is more appropriate for curve fitting nonlinear data and largefluctuation data.