To effectively implement ecosystem-based fisheries management, tools are needed that are capable of exploring the likely consequences of potential management action for the whole ecosystem. Quantitative modelling tools can be used to explore how ecosystems might respond to potential management measures, but no one model can reliably forecast all aspects of future change. To build a robust basis for management advice, a suite of models can be used, but the interpretation of the joint output of multiple models can be difficult. We employ a newly developed ensemble approach to integrate five different ecosystem models and estimate changes in ecosystem state within a single probabilistic forecast. We provide evidence on the response of ecosystem state (measured using ecological indicators relating to plankton, fish and top predators) to potential fisheries management scenarios. We demonstrate that if future fishing mortality is consistent with maximum-sustainable-yield policy, the North Sea fish community will recover in terms of its size structure and species composition. However, there is currently large uncertainty in trends of future fish biomass, plankton and top predators. We conclude that (1) this ensemble approach can be applied directly to policy-relevant questions and add value for decision makers, as multiple aspects of uncertainty are considered; (2) future research should prioritise improvements in model skill via a reduction in uncertainty surrounding biomass estimates; and (3) fisheries management that leads to sustainable fishing levels can be considered appropriate for two crucial aspects of fish biodiversity: species composition and size structure.