Oil palm (Elaeis guineensis Jacq.) is currently cultivated on 19 million ha, and palm oil represents more than one-third of the global vegetable oil market. Addition of nitrogen (N) via legume cover crop and fertilizers is a common practice in industrial oil palm plantations, however, there is a tendency for N loss, thus contributing significantly to environmental effects. To improve the sustainability of palm oil production, it is crucial to determine which management practices minimize N losses. Continuous field measurements would be cost-prohibiting as a monitoring tool, and in the case of oil palm, available models do not account for all the potential nitrogen inputs and losses or management practices. In this context, we developed IN-Palm, a model to help managers and scientists estimate N losses to the environment and identify best management practices. The main challenge was to build the model in a context of knowledge scarcity. Given these objectives and constraints, we developed an agri-environmental indicator, using the INDIGO method and fuzzy decision trees. We validated the N leaching module of IN-Palm against field data from Sumatra, Indonesia. IN-Palm is implemented in an Excel file and uses 21 readily available input variables to compute 17 modules. It estimates annual emissions and scores for each N-loss pathway and provides recommendations to reduce N losses. IN-Palm predictions of N leaching were acceptable according to several statistics, with a tendency to underestimate nitrogen leaching. Thus, we highlighted necessary improvements to increase IN-Palm precision before use in plantations.