The production of legume crop species is severely affected by disease, imposing a significant yield loss annually worldwide. Plant resistance gene analogs (RGAs) play specific roles in plant resistance responses, and their identification and subsequent application in breeding programs help to reduce this yield loss. RGAs contain conserved domains and motifs, which can be used for their identification and classification. Nucleotide-binding site-leucine-rich repeat (NLR), receptor like kinase (RLK), and receptor like protein (RLP) genes are the main types of RGAs. Computational identification and characterization of RGAs has been performed successfully among different plant species. Here, we explain the computational workflow for genome-wide RGA identification in legumes.