Objectives: Predicting the antibiotic susceptibility phenotype from genomic data is challenging, especially for some specific antibiotics in the order Enterobacterales. Here we aimed to assess the performance of whole genomic sequencing (WGS) for predicting the antibiotic susceptibility in various Enterobacterales species using the detection of antibiotic resistance genes (ARGs), specific mutations and a knowledge-based decision algorithm.