Vicia faba (faba bean) is a globally significant cool-season grain legume valued for its high protein content, nitrogen-fixing capacity, and adaptability to diverse agro-climatic conditions. However, abiotic stresses, particularly drought, severely constrain its productivity. Transcription factors of the MYC2 superfamily play pivotal roles in regulating plant responses to abiotic stress, including drought tolerance. This study presents an integrated bioinformatics pipeline to identify, characterize, and analyze putative drought stress-responsive MYC2 genes in V. faba. Using Arabidopsis thaliana MYC2 (UniProt: Q39204) as a reference, we performed homology-based screening against the V. faba genome via Ensembl Plants BLAST. Candidate sequences underwent rigorous physicochemical profiling (ProtParam), conserved domain analysis (NCBI-CDD), motif elucidation (MEME Suite), phylogenetic reconstruction (MEGA), gene structure visualization (GSDS), and subcellular localization prediction (WoLF PSORT). Iterative filtering based on domain architecture and motif conservation yielded a high-confidence set of MYC2 candidates. Phylogenetic analysis revealed diversification across evolutionary clades, with evidence of legume-specific expansion. The majority of candidates exhibited predicted nuclear localization, acidic to mildly basic isoelectric points, and thermostable aliphatic indices consistent with transcriptional regulatory functions. Gene structural analysis revealed intron-exon architectural diversity, suggesting evolutionary divergence and potential alternative splicing regulation. This work establishes a foundational genomic framework for understanding MYC2-mediated drought stress signaling in faba bean and identifies candidate targets for future functional validation and translational breeding toward drought-tolerant cultivars.