In order to make population grow sustainable, world leaders adopted the Agenda 2030 and its 17 Sustainable Development Goals (SDG). The environmental deterioration we are suffering is causing most industrialized countries to design a regulatory response that responds to current environmental demands, reaching new agreements that reorient current modes of production. The enormous complexity of problems associated with climate change and action makes experts often come up with assumptions that fail to reflect the real world constraints to reduce such a complexity. Hence to meet several of the challenges of the Agenda 2030 the SD policies and plans become ever more crucial in which Intelligent Decision Making plays a key role. Many of the decision making problems that involves sustainability policy making and SD decision support are defined under contexts that demand the participation of many stakeholders, decision makers, experts and so on. Multi-Criteria Decision Making (MCDM) has long been used to address challenges and resolve problems associated with environmental, energy, and climate policy, and decision support systems have recently been developed, featuring the capacity to solve climate change-related MCDM problems from the perspective of multiple stakeholders. However, many of the current decision making problems that involves sustainability policy making and SD decision support are defined under contexts that demand the participation of many stakeholders, decision makers, experts and so on; in the decision making processes, hence these decision making problems become more complex. One topic that recently has grown up within decision making to deal with such a type of problems is Large-Scale Group Decision Making (LSGDM) in which, the complexity of dealing with a large number of experts implies new challenges in group decision making such as, polarization opinions, scalability and the uncertainty present in the experts’ information.