<p>This study examines the role of green ambidexterity innovation, agile supply chain, and big data analytics capability in improving the performance of sustainable supply chain management in product-based SMEs in Central Java. With a hybrid CFA-SEM-ANN approach, the first stage uses CFA-SEM to validate the instrument construct; the second stage tests the structural model with PLS-SEM; and the third stage applies ANN to examine the non-linear contribution of each indicator. The PLS-SEM results show that the three independent variables explain 63.1% of the variance in sustainable supply chain performance (<i>R</i>² = 0.631). Directly, green ambidexterity innovation (<i>β</i> = 0.089; <i>p</i> &lt; 0.001), agile supply chain (<i>β</i> = 0.078; <i>p</i> &lt; 0.001), and big data analytics capability (<i>β</i> = 0.091; <i>p</i> = 0.011) significantly influence sustainable performance; agile supply chain also mediates the effect of big data analytics capability (<i>t</i> = 2.633; <i>p</i> = 0.009). ANN analysis places the indicators “expanding existing green markets” (GA5), “ability to adjust production levels” (AG2), and “customization intensity” (AG1) as the three most important factors. Managerial implications emphasize the priority of green market expansion, increasing production flexibility, and strengthening strategic analytics frameworks to drive sustainable supply chain excellence<i>.</i></p>