Through robust Kalman filtering method, an AARMA (Adaptive Auto Regressive Moving Average) model is proposed to forecast the nonlinear and non-stationary data traffic of MMS, KJAVA and WAP of China Mobile. The forecasting results show that the AARMA model need less model parameters and has higher forecasting accuracy, and the forecasting error has the obvious characteristic of white noise.