This work presents the new integrative model CASIMOD’N (Catchment and Agricultural Systems Integrated MODel for Nitrogen), which assesses effects of farming systems on nitrogen (N) dynamics at the catchment level. Its main innovation is the consideration of the level of the farming system through production strategies, farmer decisions and the expression of decisions as management practices, along with the link between these farming systems, their practices and water pollution. CASIMOD’N integrates farming systems at the farm level and N transfers and transformations at the field, farm and catchment levels. It was built by adapting and combining three models: the catchment-scale biophysical model TNT2 and two farm-scale models, TOURNESOL and FUMIGENE, for the allocation of land use and manure, respectively. The intrinsic logic behind farming system design and function was represented by ensuring agreement between livestock-feeding and manure-management strategies under specific farm constraints (land fragmentation, distance between fields and farmyards)and agronomic rules. The model is able to simulate management practices (crop, manure and mineral fertiliser allocation). An assessment of the farming system modelling was performed by comparing the management practices simulated with CASIMOD’N with (i) observed data from a livestock-oriented catchment and (ii) a reference dataset of management practices reconstructed with a Markov chain and Knapsack-based algorithm. Then, the spatial distributions of the main N fluxes at the sub-catchment scale simulated with CASIMOD’N and based on the reconstructed management practices are discussed. Simulations of the two options had few differences in spatial distribution of the main N compartments, organic and mineral fertilisation and N flux at the outlets both at catchment and sub-catchment levels. However, CASIMOD’N was more accurate for simulating farming systems than the reconstructed reference dataset of management practices. This suggests that CASIMOD’N can be used to conceive, implement and assess prospective scenarios involving farming system redesign.