This study examines the implementation of lean-agile (leagile) supply chain strategies in Kenyan humanitarian organizations, assessing their impact on operational performance with organizational characteristics as moderators. A census survey of 330 humanitarian aid organizations in Kenya was conducted, achieving an 87.88% response rate (290 organizations). Using moderated multiple regression and Grey Incidence Analysis, the research tested five hypotheses linking supply chain responsiveness, resilience, efficiency, integration, and organizational characteristics to performance outcomes. Results revealed that leagile dimensions collectively explain 71.9% of performance variance (R²=0.719), with responsiveness (β=0.532), efficiency (β=0.415), and integration (β=0.458) showing strong positive effects. Organizational characteristics—size, structure, and age—moderated these relationships, increasing the explanatory power to 82.7% (R² = 0.827). The study validates Grey Incidence Analysis as a robust framework for managing uncertainties in humanitarian "grey systems" and integrates organizational theory into supply chain leagility research. Practically, it advocates for full leagile adoption, emphasizing decentralized decision-making, AI-driven forecasting, and technologies like IoT and blockchain to enhance coordination and resilience. Despite high donor funding, Kenya’s Arid and Semi-Arid Lands (ASALs) face persistent inefficiencies, underscoring the need for localized capacity-building and multi-stakeholder collaboration. Limitations include reliance on self-reported data and a cross-sectional design, suggesting future longitudinal studies and beneficiary feedback integration. This work contributes empirical evidence on hybrid supply chain strategies in humanitarian contexts, offering actionable insights for policymakers and practitioners to optimize disaster response in resource-constrained environments.