<p>Increasing environmental, social, and economic pressures have compelled small and medium enterprises (SMEs) to pursue ambidextrous strategies that balance exploitation of existing supply chain capabilities with exploration of sustainable innovations. This study develops an integrative framework for assessing Sustainable Supply Chain Ambidexterity (SSCA). It is combining the Best-worst Method (BWM), fuzzy logic, and the Capability Maturity Model (CMM). Fifteen SSCA indicators were identified across economic (supply chain ambidexterity), environment (green ambidexterity innovation), and social (employee ambidexterity) dimensions. The BWM results reveal that economic ambidexterity receives the highest weight (0.501), followed by environmental (0.294) and social (0.205) dimensions. Among fifteen indicators, product innovation (AM1: 0.124) and supplier collaboration (AM5: 0.113) rank as the top priorities, while cross-functional collaboration (EA4: 0.029) ranks lowest. The SSCA Maturity Index across ten SME cases ranges from 3.046 to 5.042, with nine SMEs positioned at the “Defined” level (3.01–5.00) and one SME achieving “Managed” level (5.042). The proposed hybrid BWM-Fuzzy-CMM approach advances both theory and practices by (i) providing a benchmarking index to prioritize SSCA indicators, and (ii) offering a maturity roadmap that captures SMEs’ staged progression toward sustainability ambidexterity. The findings highlight a resource-driven prioritization path, where economic imperatives anchor the transition toward environmental and social dimensions. Managerially, the framework enables SMEs to allocate resources efficiently by targeting high-weight indicators (e.g., AM1 and AM5) and systematically advancing from Defined to Optimizing maturity stages, with a specific roadmap to elevate employee ambidexterity which currently contributes only 0.205 to the SSCA index. However, findings are context-bound to Indonesian SMEs, requiring cross-cultural validation before broader generalization.</p>