The identification of pathogens is essential for effective surveillance and outbreak detection, which has been facilitated by the decreasing cost of whole-genome sequencing (WGS). However, extracting relevant virulence genes from WGS data remains a challenge. In this study, we developed a web-based tool to predict virulence-associated genes in enterotoxigenic Escherichia coli (ETEC), including heat-labile toxin (LT) genes (eltA and eltB), heat-stable enterotoxin (ST) genes (est) for both human and animal, enterotoxin (espC), colonization factors CS1 through 30, F4, F5, F6, F17, F18, and F41, and toxigenic invasion and adherence loci (tia, tibAC, etpBAC, eatA, yghJ, and tleA). To construct the database, we revised the existing ETEC nomenclature and used the VirulenceFinder webtool at the CGE website (https://cge.cbs.dtu.dk/services/VirulenceFinder/). The database was tested on 1,083 preassembled ETEC genomes and the ETEC reference sequence for strain H10407. We added 455 new alleles, replaced or renamed 50 alleles, and removed two. Overall, our tool has the potential to greatly facilitate ETEC identification and improve the accuracy of WGS analysis. The revised nomenclature and expanded gene repertoire provide a better understanding of the genetic diversity of ETEC. Additionally, the user-friendly interface makes it accessible to users with limited bioinformatics experience.