In this paper, we present new ProxyMeans Test (PMT) models for targeting based on the 2017household survey data (EDAM4). The paper finds that thedeveloped PMT models, with separate targeting formulas forrural and urban areas, appear to perform well vis-a-visinclusion and exclusion errors observed in similar countrycontexts. Ex-ante simulations also show that the plannedexpansion of targeted social assistance program, PNSF, usingthe proposed targeting approaches will result in nearly 0.7percentage point reduction in poverty nationally and 3.4-4.1 percentage reductions in the regions. These resultsreinforce the effectiveness of PMT targeting approach forsocial assistance programs in Djibouti when carried out incombination with geographic targeting in high-povertydistricts. The results also show the relevance andeffectiveness of PMT as a national targeting approach inurban regions and for an expanded national social assistance program.