This study proposes an applied multi-criteria decision-making framework for prioritizing school reconstruction in post-conflict environments under epistemic uncertainty. The framework synthesizes policy-driven preferences via Fuzzy Analytic Hierarchy Process (FAHP) with objective data dispersion using Entropy weighting, integrated into a TOPSIS ranking model. The methodology is applied to the Gaza Strip using fully observed data from official Palestinian and international sources (PCBS 2023, MoE 2025, OCHA 2025–2026), covering 796 schools and 608,364 students. To evaluate ranking robustness under weight uncertainty, a Dirichlet-based stochastic perturbation (10,000 simulations) is employed. A Bootstrap Rank Stability Index (BRSI) is defined as the probability that an alternative maintains its exact rank position under perturbation. Results indicate very high stability: Gaza governorate retains top rank in approximately 99% of simulations, Khan Yunis in approximately 98%. Kendall’s W computed over aggregated rank frequencies is 0.94. Sensitivity analysis shows top-three rankings invariant to ±30% weight perturbations (Spearman’s ρ > 0.98). Results remain invariant across Dirichlet concentration parameters λ ∈ [5,50]. A three-phase operational roadmap is proposed with approximate allocation ranges (e.g., 60–70% of expected budget for top priorities). The framework provides a transparent, reproducible tool for humanitarian resource allocation under severe uncertainty.