Statkraft requires projections of future streamflow to plan hydropower investments. Setting up a hydrological model for new regions can be too time-consuming to meet the often short delivery deadlines. We have developed an interpretable machine learning method that links streamflow to precipitation and temperature, and can serve as a first screening approach. This method is then applied to climate model simulations of precipitation and temperature to obtain streamflow projections for Brazil.