OBJECTIVES: To explore the cost-effectiveness of bacterial whole-genome sequencing (bWGS) in determining antibiotic resistance and selecting antibiotics for treatment of urinary-tract infections (UTI), from the perspective of the UK National Health Service. METHODS: A decision-tree model was developed to compare the cost-effectiveness of UTI treatment with or without bWGS. Nitrofurantoin (NTF), trimethoprim and co-amoxiclav were designated as first-, second- and last-line treatments respectively, in accordance with treatment guidelines. Parameters extracted from peer-reviewed literature included the prevalence of resistance and disease-state utilities. Duration and cost of treatments were taken from the British National Formulary. The cost and time to perform bWGS for a complete E. coli genome using the MiSeq platform were estimated. The incremental cost-effectiveness ratio was calculated as cost (GBP) per quality-adjusted life-year (QALY). Threshold analyses were performed to explore scenarios where bWGS could become a cost-effective strategy. RESULTS: Using a current prevalence of resistance to NTF of 5.3% and a cost per genome of £39.69, bWGS was dominated; being more expensive and with worse health outcomes than current clinical practice. However, an ~80% reduction in cost of sequencing would lead to bWGS being cost-saving compared to current practice. Alternatively, if NTF resistance prevalence increased to 44%, bWGS could become cost-effective at £20,000/QALY. Under some scenarios, such as a reduced bWGS cost of £15 per genome and increased NTF resistance prevalence of 25%, bWGS would become a dominant strategy; being less expensive with better health outcomes than current practice. CONCLUSIONS: Currently bWGS is not likely to be a cost-effective option for directing the selection of antibiotics in the treatment of UTIs; however, in the probable situation that the cost of sequencing decreases and resistance to first line antibiotics increases, bWGS is expected to become a cost-effective or dominant option. This technology therefore has great potential for improving antibiotic stewardship.