The escalating demand for reliable and sustainable energy has positioned micro-hybrid renewable energy systems (MHRESs) as promising alternatives to conventional, cost-intensive power generation infrastructures. However, identifying an optimal MHRES configuration involves complex trade-offs among conflicting technical, economic, environmental, and social criteria, which are often compounded by epistemic uncertainty and subjective expert judgments. To address these challenges, this study develops a novel multi-criteria group decision-making (MCGDM) framework under an intuitionistic fuzzy environment. The proposed methodology comprises three interconnected phases: (i) an intuitionistic fuzzy compromise solution (IF-CS) model to objectively determine decision-makers’ weights, (ii) an integrated IF-ANP-DEMATEL approach to capture interdependencies and causal feedback among sustainability criteria, and (iii) an IF-utility-degree formulation to prioritize candidate configurations. To demonstrate its practical applicability, the developed framework is applied to an off-grid case study evaluating various hybrid configurations, including solar, wind, and diesel-battery systems. The obtained results indicate that the Photovoltaic/Wind/Battery system achieves superior overall performance, primarily driven by lifecycle economic efficiency, minimized net present cost, and low power-interruption risk. Finally, comparative analyses with existing intuitionistic fuzzy benchmark methods along with comprehensive sensitivity analyses validate the robustness, stability, and managerial efficacy of the proposed decision-support model for sustainable energy planning.