Forests have been the primary source of fibers, food, water, biodiversity, energy, recreation, scenic beauty, and environmental services. Forest management science encompasses the challenge of working with forests in a way that produces required benefits now without compromising future benefits and choices. The concept of optimized forest management has become broader in recent decades. Pressure toward social, economic, and environmental sustainability pushes up research to cover these demands by improving models, introducing new methods, and adding holistic planning approaches in forest management decision support systems (FMDSS). The conflicts that arise between the desire to consume natural resources and the desire to preserve them make the multicriteria decision theory necessary. Brazil, one of the ten largest timber producers in the world, has the second largest forest cover on the planet. It also uses optimization models that represent the growth of forests integrated with decision support systems that assist managers in their decisions. However, forest planning models and applied decision support systems are not uniformly developed and available for all types of problems encountered in the country. Brazilian forest plantation managers have to face many conflicts when continuously seeking gains regarding efficiency (higher productivity at lower costs) and efficacy (higher profits with minimum social and environmental impacts).Leading producing countries on timber, pulp, and fiberboard have their managers constantly interact to fine-tune industry processing demands vis-a-vis the demands of highly productive fast-growing forest plantations. The decision process in such cases seeks a compromise that accommodates frequently conflicting objectives. Therefore, this research work aims to develop a forest management decision support system (FMDSS) based on multicriteria decision-making (MCDM) techniques to support group decision-making (GDM) in the diversified context of forest plantations in Brazil. Explicitly, the objective is developing a set of models to optimize forest management embedded in a DDS to meet the needs of the decision-makers of the different types of forest plantation organizations that operate in Brazil. This set of models encompasses multicriteria mathematical programming models, processes, and data models structured in such a way to be versatile enough to support interactive group decision-making.