Abstract: Monthly predictions for eight winter months during 1976-1977 and 1982-1983 El Nino events were performed by using a three-layer anomalous filtered model (AFM) in which transient Rossby waves were filterd.The results show that this model predicts successfully the large-scale patterns of the monthly mean surface temperature anomalies.The correlation coefficients between the observations and the predictions are higher than those of persistence predictions.By comparison with the anomalous general circulation model (AGCM) the AFM gives almost identical results,but the computer time required for running the AFM is almost 100 times less than that required for running the AGCM.It is also shown that the results of the three-layer model are better than those of the one-layer model.In the meanwhile,four seasonal forecasts were also carried out by using the same model.It seems to be shown that the AFM possesses potential ability in predicting seasonal large scale circulation anomalies.