Recently the inadequacy of planning and forecasting techniques for innovations with high levels of uncertainty has become a subject of intense research. In this paper a stochastic approach is presented which integrates uncertainty in a foresight methodology based on multi-dimensional quantitative key performance indicators (KPIs). A Monte Carlo Simulations delivers the prognoses of the KPIs based on a system model and stochastic input parameters. The new foresight methodology is applied to identify the best future electric bus system for the city of Berlin which will be realized within the e-mobility showcase program of the German federal government. The methodology is evaluated by expert interviews regarding its value added, limitations and the applicability in other use cases.