Leishmaniasis is a neglected tropical disease with a significant global health burden, particularly in developing countries, where it accounts for approximately 1.6 million new infections annually. Current therapeutic options are limited by severe adverse effects, toxicity, and drug resistance, highlighting the urgent need for novel treatment strategies. Arginase from Leishmania spp. (LamARG) has been identified as a promising therapeutic target due to its pivotal role in parasite survival and proliferation. Drug repurposing offers a strategic advantage by accelerating the identification of new therapeutics with established safety profiles, as demonstrated by repurposed agents such as miltefosine, amphotericin B, and paromomycin. This study aimed to identify FDA-approved drugs with inhibitory potential against LamARG, leveraging structure- and ligand-based computational approaches. A three-dimensional model of LamARG was constructed through comparative modeling, followed by the compilation of known inhibitors from the literature. Molecular docking analyzed their binding interactions, generating pharmacophore hypotheses. These models were validated and applied for virtual screening of FDA-approved compounds from the e-Drug 3D database. Hits identified through pharmacophore-based screening were further evaluated using molecular docking and molecular dynamics simulations to elucidate their binding modes and stability within the catalytic site of LamARG. Our findings indicate that Dabigatran exhibits strong binding affinity and key interactions within the active site of LamARG, suggesting its potential as a viable therapeutic candidate. With strong binding affinity, oral bioavailability, and a well-established safety profile, Dabigatran emerges as a promising repurposed drug against cutaneous leishmaniasis, offering a novel, patient-friendly therapeutic option to overcome treatment limitations and resistance challenges.