This study examines the determinants of household welfare in post-conflict South Sudan using cross-sectional econometric analysis of 3,550 households across six states and 50 enumeration areas in 2015. In a context where over 80% of the population lives in poverty following decades of conflict, understanding vulnerability-welfare relationships becomes critical for effective policy intervention. Employing state fixed effects models with cluster-robust standard errors, we identify statistically significant vulnerability effects on household welfare outcomes, with vulnerable households experiencing welfare scores 10.97 percentage points lower than those of non-vulnerable households (t-statistic = 31.98). The analysis reveals important asset-vulnerability interactions, with the negative impact of vulnerability diminishing as household asset levels increase, suggesting compound disadvantages for asset-poor vulnerable households. Robustness checks, including bootstrap validation, alternative clustering approaches, and different welfare measures, confirm the consistency of core findings across specifications. Policy targeting simulations indicate potential efficiency gains of 20% through improved welfare-based targeting mechanisms compared to current vulnerability-based approaches. Optimal targeting achieves 100% efficiency at 10% coverage, whereas current methods reach 85.7% efficiency. Heterogeneous effects analysis reveals that vulnerability impacts vary significantly across asset groups, with high-asset households showing the strongest vulnerability effects.