A question of environmental risks of social and economic infrastructure has become apparent recently due to an increase in the number of extreme weather events. Extreme runoff events include floods and droughts. In water engineering extreme runoff is described in terms of probability, and uses methods of frequency analysis to evaluate an exceedance probability curve (EPC) of runoff. It is assumed that historical observations of runoff are representative for the future; however trends in observed time series doubt this assumption. The paper describes an Advance Frequency Analysis (AFA) approach to be applied to predict future extreme runoff. The approach combines traditional methods of hydrological modelling and frequency analysis, and results in a probabilistic hydrological model markov Chain System (marcs). The MARCS model simulates statistical estimators of a multi-year runoff to perform future runoff projections in probabilistic form. Projected statistics of meteorological variables available in climate scenarios force the MARCS model. This study introduces a new model core (version 0.2), and provides an user guide as well as an example of the model set up for a single case study. In this case study, the model simulates projected exceedance probability curves of annual runoff under three climate scenarios. The scope of applicability and limitations of the model are discussed.