As the volume and complexity of data continue to grow, intelligent information systems are increasingly applied to support decision-making. Their expanding use in the domain of multi-criteria decision-making has fostered the development of numerous frameworks that combine diverse methods and tools, including multi-criteria decision analysis (MCDA) techniques and machine learning (ML) models. This study introduces a framework that integrates MCDA with ML models to capture decision-makers’ preferences and, based on these, predict country rankings related to the achievement of Sustainable Development Goal 7. The findings demonstrate that the proposed approach provides a practical and effective alternative for multi-criteria evaluation in situations where expert knowledge is unavailable, thereby addressing the limitations of traditional MCDA methods that depend on the direct involvement of decision-makers and stakeholders.