Present-day drought early warning systems only provide information on drought hazard forecasts. Here, we have developed drought impact functions to forecast drought impacts up to 7 months ahead using machine learning techniques, logistic regression, and random forest. Our results show that random forest produces a higher-impact forecasting skill than logistic regression. For German county levels, drought impacts can be forecasted up to 4 months ahead using random forest.