Quality of operational flood forecasting system (FFS) is the essential component for efficient response to the foreseen flood events. The thesis is describing why FFS is needed, how does it help, what are its parts and how does it influence the response process. But the basic question is how well the results are. In the last ten years, Slovenian floods demanded extremely high costs. To address this costly water power the development of FFS is part of nonstructural measures to reduce the flood impact. Achieving good forecasts is mostly connected to hard work in verification and learning from the models results. Therefore, it is crucial to define the methodology for operational control of the model formation to ensure continuity and improvement of its operation. FFS consists of several parts, which are interconnected and interdependent. The system requires and operational monitoring network, hydrologic model, hydrodynamic model, meteorological models, visualization and presentation of the results and last but not least the analysis of quality, efficiency, accuracy, reliability and skill. Methods of analysis are very alike and each provides target identification and presentation of the shortcomings of the results. In the analysis, deterministic and continuous analyses were used. As most efficient was proven the relative operating characteristics (ROC), which shows the relative probability of correct prediction. Verification indexes as Nash-Sucliffe efficiency (NSE) or Kling-Gubta efficiency (KGE) are seen as more useful in calibration process and binary success indexes are hydrologically seen often more appropriate for uniform discharge distributions.