Europe is currently experiencing an increase in the severity and frequency of summer drought events driven by global warming. Forecasting these seasonal events months in advance is a crucial tool for effective environmental planning and the mitigation of environmental and socio-economic impacts. However, accurate prediction of European summer droughts remains a significant challenge for seasonal forecast models. This thesis aims to investigate the predictive skill of the fifth-generation seasonal forecast system (SEAS5), developed by ECMWF, regarding summer drought events in Europe. To detect and quantify these events, the Standardized Water Balance Anomaly (SWBA) index was employed. This index is derived from the atmospheric water balance—the difference between precipitation and potential evapotranspiration.