An early warning system for drought events can provide valuable information for decision makers dealing with water resources management and international aid. However, predicting such extreme events is still a big challenge. In this study, we compare two approaches for drought predictions based, respectively, on forecasted precipitation derived from the extended ENSemble system of the ECMWF, and on forecasted Monthly Occurrence Anomaly of Weather Regimes (MOAWRs) also derived from the ECMWF model. Results show that the MOAWRs approach outperforms the one based on forecasted precipitation in winter in the northern and eastern parts of the European continent, where more than 65 % of droughts are detected one month in advance. While, the approach based on forecasted precipitation achieves better performance in predicting drought events in central and eastern Europe in both spring and summer, when the local atmospheric forcing could be the key driver of the precipitation. Sensitivity tests also reveal the challenges in predicting small-scales and onset drought events at longer lead times. Finally, in most of the cases, the ENSemble system of the ECMWF successfully represents the observed large scale atmospheric patterns, depicted by the MOAWRs, associated with drought events over Europe.