Abstract: In this study Artificial Neural-networks is employed to predict the CO concentration during 2002 to 2004. The application of the multiple perceptron with back-propagation learning algorithm is reported in the prediction eleven sites at one site. The generalization ability of the model is confirmed by root mean square error and correlation between observed and predicted concentrations. The evaluation of model results shows that the degree of success in forecasting CO concentration is promising.