In response to the increasing complexity of urban and architectural projects and the need for informed, viable, and objective problem-solving processes, this research examines the decision-making processes in urban and architectural realms. In particular, it explores how artificial intelligence (AI) can enhance specific stages of decision-support approaches. Through a combination of theoretical analysis with practical application, this thesis explores the use of Multi-Values Appraisal Methodology (MuVAM) to support decision-making in architecture with or without the support of artificial intelligence (AI). MuVAM is a new tool that combines problem structuring methods (PSMs) and multi-criteria decision analyses (MCDAs), offering a framework to address complex problems and evaluate multiple criteria.