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Investor-Owned Utilities (IOUs) serve as pivotal actors in the U.S. electricity sector, wielding substantial influence over infrastructure investment, pricing strategies, and clean energy adoption—decisions with far-reaching implications for energy justice. Despite the growing prominence of energy justice in academic and policy discourse, empirical research exploring the causal pathways that shape recognition, procedural, and distributional justice outcomes in utility governance remains limited. This study introduces a novel, multidimensional Energy Justice Index (EJI) and applies a two-stage analytical strategy across the full population of 166 IOUs. Stage one uses machine learning (Decision Trees, Random Forests) to identify salient predictors from 30 theory-informed variables, including institutional, regulatory, and market conditions. Stage two employs structure-learning algorithms (NOTEARS and CAM) to uncover conditional dependencies and interaction pathways across diverse regulatory environments. Preliminary results indicate that strong state commitments to renewable energy and the presence of equitable governance provisions—such as public advisory group requirements, intervenor compensation, and equity-focused cost-effectiveness tests—consistently emerge as upstream drivers of improved recognition and procedural justice outcomes. In contrast, distributional outcomes are more closely associated with utility-level financial characteristics, including capital expenditures and the ratio of residential to commercial rates, with regulatory capture mediating institutional effects. Causal graphs reveal that stakeholder inclusion moderates the influence of clean energy mandates, while longer commissioner tenure strengthens stable equity-enhancing pathways by reinforcing institutional continuity. These findings highlight the configurational nature of energy justice, suggesting that outcomes are not attributable to single policies or structures, but to context-dependent interactions among regulatory design, utility behavior, and institutional capacity—advancing a causal understanding of justice in utility-sector governance.