Abstract Routine clinical chemistry data are widely collected in medical settings, yet their potential for lifestyle characterization using multivariate analysis remains underexplored. Leveraging these routinely available measurements could provide a cost-effective strategy for identifying lifestyle-related biochemical patterns at the population level. In this study, a range of linear and non-linear multivariate classification methods were evaluated to discriminate between smokers and non-smoker