Dilated cardiomyopathy (DCM) is associated with shifts in cardiac metabolism. Those shifts are inconsistent between patients, possibly due to heterogeneity in DCM etiologies. Identifying metabolic subtypes, or metabotypes, in DCM patients may open personalized treatment opportunities. Developing a methodology to identify metabotypes would be a boon in this regard. Here, we describe a metabotyping pipeline, integrating advanced metabolic modeling methods optimized for cardiac research, to uncover these subtypes using widely available transcriptomics data. We applied our method to publicly available cardiac data of end-stage DCM patients and non-failing controls, identifying two metabotypes in the DCM group. These metabotypes are characterized by unique metabolic alterations, notably in calcium handling, amino-acid oxidation, and the pentose phosphate pathway. Strikingly, one metabotype exhibited a greater deviation from healthy controls, suggesting a greater metabolic contribution to its underlying etiology. Further transcriptome-wide analysis revealed immune-related differences between metabotypes, suggesting an interplay between inflammation, immune response and metabolism in these DCM subtypes. Our study uncovers cardiometabolic heterogeneity in DCM and underscores the potential of transcriptome-derived metabotyping in cardiovascular research.