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Decision Support Systems are seen as particularly useful for unstructured, ill-structured and semi-structured problems where human judgement is relevant for problem solving and limitations in human information processing may impede the decision making process. Decision making situations that involve many stakeholders and different natural resources require therefore tools that facilitate the inclusion of stakeholder preferences on different management objectives in the decision making process. On a European scale the reduction in net emissions of greenhouse gases, the sustainable use of forest resources and provision of forest ecosystem services as well as the integration of different economies and societal values are demanded from different stakeholders and policy. The OptFor-EU project “OPTimising FORest management decisions for a low-carbon, climate resilient future in Europe“ designs a Decision Support System that provides forest managers with options for climate resilent forests, decarbonisation and many other forest ecosystem services. The DSS will help stakeholders to select, understand, and undertake appropriate actions to increase forest carbon sinks under changing climate conditions, whilst ensuring other important ecosystem services are maintained or enhanced. The process is decomposed in four basic steps: (1) problem identification and diagnosis, (2) searching and designing for options to overcome the problem, (3) screening and estimation of the effects of different treatment options, (4) evaluation and analysis of various alternative courses of actions. Based on this process, the decision maker can choose an alternative forest management option for a low-carbon, climate resilient future, and analyse the effect of different preferences for the mangagement objectives or climate change projections. The DSS is designed as a “toolbox” by integrating database management systems with analytical and operational research models, graphic display, tabular reporting capabilities to support decision making. A set of climate sensitive forest models were used to predict the effects of different forest management practices (FMP) under various climate change scenarios. The forest stands are characterized based on a European wide classification of European forest types (e.g. beech forest, alpine forest). Users can select from a novel set of Essential Forest Mitigation Indicators (EFMI) and explore their performance for a particular temporal (e.g. 10, 20 years) and spatial (national, regional) scale. For the evaluation of FMPs the preferences for selected EFMIs can be defined and the synergies or trade-offs among the alternatives evaluated. In this contribution the basic components of the DSS (Explorer, Evaluator, Data Client and Database) and their functionality are demonstrated for one of the eight case studies in Europe.