Deciding on which crop to plant on a field and how to fertilize it has become increasingly complex as volatile markets, location factors as well as policy restrictions need to be considered simultaneously. To assist farmers in this process, we develop the web-based, open source decision support system ‘Fruchtfolge’ (German for ‘crop rotation’). It provides decision makers with a crop and management recommendation for each field based on the solution of a single farm optimization model. The optimization model accounts for field specific location factors, labor endowments, field-to-farm distances and policy restrictions such as measures linked to the EU Nitrates Directives and the Greening of the EU Common Agricultural Policy. ‘Fruchtfolge’ is user-friendly by automatically including big data related to farm, location and management characteristics and providing instant feedback on alternative management choices. This way, creating a first optimal cropping plan generally requires less than five minutes. We apply the decision support system to a German case study farm which manages fields outside and inside a nitrate sensitive area. In the year 2021, revised fertilization regulations come in force in Germany, which amongst others lowers maximal allowed nitrogen applications relative to crop nutrient needs in nitrate sensitive areas. The regulations provoke profit losses of up to 15% for the former optimal crop rotation. The optimal adaptation strategy proposed by ‘Fruchfolge’ diminishes this loss to 10%. The reduction in profit loss clearly underlines the benefits of our support tool to take optimal cropping decisions in a complex environment. Future research should identify barriers of farmers to apply decision support systems and upon availability, integrate more detailed crop and field specific sensor data.