A handy method of forecasting the ionospheric TEC one hour ahead by Artificial Neural Network (ANN) is presented in this paper. Considering of the practical application, the observations of TEC are used as inputs without any other data. The input parameters are the present observation of TEC, the first difference and relative difference of TEC, and the local time. The output is the TEC one hour ahead. Ionospheric TEC data evaluated from GPS measurements at Xiamen receiving station is used to checkout the forecasting method. The relative error is 9.3744%, and the cross correlation coefficient between the observed and forecast TEC values is 0.96678. The accuracy rate of relative error less than 15% is 79.59%, during the geomagnetic storms, but 98.81% for the quiet or moderate geomagnetic conditions. These conclusions suggest that the value of forecasting is very the geomagnetic level. It is shown that the Artificial Neural Network is promising in forecasting of ionospheric TEC one hour ahead.