© 2015 Elsevier Inc. This study aims to evaluate the robustness of clinical and metabolic phenotyping through, for the first time, the identification of differential responsiveness to dietary strategies in the improvement of cardiometabolic risk conditions. Clinical phenotyping of 57 volunteers with cardiovascular risk factors was achieved using k-means cluster analysis based on 69 biochemical and anthropometric parameters. Cluster validation based on Dunn and Figure of Merit analysis for internal coherence and external homogeneity were employed. k-Means produced four clusters with particular clinical profiles. Differences on urine metabolomic profiles among clinical phenotypes were explored and validated by multivariate orthogonal signal correction partial least-squares discriminant analysis (OSC-PLS-DA) models. OSC-PLS-DA of 1H-NMR data revealed that model comparing