This work explores the applicability of widely known fuzzy time series forecasting techniques for the prediction of wind and wave data. These techniques have extensively been used with great success to the forecasting of stock prices. In the present work, long-term time series of wind speed, significant wave height, and peak period are examined and used for the verification of the forecasting performance of the fuzzy models. To examine the forecasting accuracy, the root mean squared error (RMSE) is used as an evaluation criterion to compare the forecasting performance of the listing models. As the importance of quality of wind and wave data increases, effective forecasting could further benefit designers of offshore structures and environmental researchers.