This paper presents an application of a new system modeling algorithm using neural fuzzy technique. The model is intended to forecast power transformer temperature characteristics in order to predict its behaviour. The forecast accuracy is compared with the IEEE and Massachusetts Institute of Technology (MIT) models. The real data from an 8000kVA power tranformer have been used for training and testing the models. Results show that the intelligent neural fuzzy model has achieved a better prediction against the IEEE and MIT models.