Wave prediction is one of the most important issues in coastal and ocean engineering studies. In this study, the performance of Adaptive-Network-Based Fuzzy Inference System (ANFIS) and Coastal Engineering Manual (CEM) methods for predicting wave parameters were investigated. The data set used in this study comprises of fetch-limited wave data and over water wind data gathered from deep-water location in Lake Ontario. The data set of year 2002 was used to develop the ANFIS models as wave predictor models. The data set of year 2003 was then used to test the developed ANFIS models and also the CEM method. Results indicate that ANFIS outperforms the CEM method in terms of prediction capability as the scatter index of predictions of ANFIS is less than that of CEM method. In particular, the CEM method overestimates the significant wave height and underestimates the peak spectral period, while ANFIS results in more accurate predictions.