Lake Van is one of the largest terminal lakes in the world. In recent years, significant lake level fluctuations have occurred and can be related to global climatic change. This fluctuation sometimes exhibits abrupt shifts. Floods originating from the lake can cause considerable damage and loss in agriculture and urban areas. Therefore, water level forecasting plays a significant role in planning and design. This study is aimed at predicting future lake levels from past rainfall amounts and water level records. A dynamical change of the lake level is evaluated by the fuzzy approach. The fuzzy inference system has the ability to use fuzzy membership functions that include the uncertainties of the concerned event. This method is applied for Lake Van, in east Turkey. Furthermore, model capabilities are compared with ARMAX model. It is shown that lower absolute errors are obtained with the Takagi-Sugeno fuzzy approach than with the ARMAX model.