Abstract: A system and method for representing and incorporating available information into uncertainty-based forecasts is provided. The system comprises a new class of models able to efficiently and effectively represent uncertainty-based forecasts with a wide range of characteristics with greater accuracy. Further, methods provide for selection of a most appropriate model from the class of models and calibration of the selected model to all available data, including both directly relevant historical data and expert opinion and analysis. An output is a model that can be used to generate an uncertainty-based forecast for a variable or variables of interest accurately and efficiently. In addition, methods for refining input data and testing and refining the output representation of the uncertainty-based forecast are provided.