Feed accounts for more than half of production costs and environmental impacts of the pig industry. The use of a greater diversity of feedstuffs, often more local but less digestible is one lever to mitigate these impacts. However, current pigs value better energy-rich and easy to digest diets. Thus, the multiperformance of different pig profiles in production systems differing for their feeding constraints should be characterized. The objective of this study is to propose a modelling approach to evaluate how different production systems affect the multiperformance of different individual pig profiles. Four contrasted systems were considered: (1) conventional system (CS) representative of standard practices in French pig farms, (2) CS excluding raw materials with high environmental impacts and including low-cost opportunity feedstuffs, (3) CS with local feedstuffs, and (4) an organic system with fodder. A dataset of 1,586 InraPorc® pig profiles was established from a previous trial. Feeds were formulated to cover individual nutritional requirements given the constraints of each system. Two formulation objectives were applied: a least-cost formulation, as commonly used, and a multi-objective formulation that minimizes feed environmental impacts under an economic constraint on feed price. We simulated, in each system and for each formulation objective, responses from these 1,586 pig profiles, using a previously published individual-based model of the pig fattening unit. The model provides animal performance and environmental impacts evaluated through a cradle-to-farm-gate life cycle assessment (LCA): climate change, resource use (fossils, minerals and metals), acidification, marine, freshwater and terrestrial eutrophication and land occupation. Based on these indicators, the 1,586 pigs can be ranked on their technical and environmental performances in each system, to identify which individual profiles fit best in each breeding system, and if G×E occurred. To conclude, combining system and individual level modelling provides a strategy to predict the multiperformance of pigs in a variety of systems, that could later be used to identify individual profiles adapted to each system.