Several studies have demonstrated that an integrated approach to the airline schedule recovery problem, optimising multiple facets simultaneously rather than using traditional sequential methods, yields improved solution quality; however, at the cost of model simplification, with most studies focusing solely on cost minimisation. This paper introduces a multi-objective Benders decomposition approach to a detailed integrated aircraft and crew recovery model that considers a heterogeneous fleet, individual crew members, and basic passenger considerations, thereby addressing both model simplifications and lack of multi-objective considerations. A lexicographic multi-objective optimisation scheme is integrated into Benders decomposition, allowing for the optimisation of multiple distinct objectives: minimising cancellations, minimising recovery costs, maximising on-time performance, and minimising changes made. Computational tests were conducted using real schedule data provided by Transavia, with results showing high-quality solutions within the model’s defined assumptions. However, Benders decomposition alone was insufficient to be applicable within live disruption management, with performance times ranging from 5 to 30 minutes depending on the scenario’s complexity. The model’s design and ability to consider crew on an individual level show strong promise in solution quality and applicability to the industry, as crew are often considered at both the pairing and individual levels. This provides a strong foundation for practical disruption management support tools if deficiencies in time performance can be addressed.