Marine ecosystem and the services which they supply are under threat from a wide range of human activities. In order to achieve sustainability, an ecosystem-based approach to fisheries management (EBFM), i.e., integrating multiple drivers in a common framework is therefore needed. The overarching aim of this thesis is to develop a decision-support tool fit for achieving EBFM in the Central Baltic Sea, an ecosystem heavily impacted by overfishing and climate change. To that end, a theoretical approach for modelling multispecies population dynamics was combined with advanced statistical methods in order to develop a stochastic food-web model integrating species interactions, between cod and the forage fish species herring and sprat, with external forcing through commercial fishing, zooplankton and climate effects. Furthermore, by linking models across sectors, i.e., with climate and bio-economical models, we were able to account for management consequences over a wide range of policy objectives and define overall ecologically and economically optimal management solutions. To that end, our coupled modelling tool demonstrates how by adopting an ecosystem approach we may quantitatively forecast the response of Baltic fish stocks to climate change and take appropriate management actions to mitigate negative effects on future fisheries production. Furthermore, by presenting the ecological need and economic advantage of our ecosystem-based approach we may establish the institutional and political will necessary for successful implementation of EBFM in the Baltic Sea, a vital first step towards achieving long-term sustainability in marine fisheries worldwide.