Cellular morphology has the capacity to serve as surrogate for cellular state and functionality. However, primary cardiomyocytes, the standard model in cardiovascular research, are highly heterogeneous cells and thereby impose methodological challenges to analysis. Hence, we aimed to devise a robust methodology to deconvolute cardiomyocytes’ morphology on a single cell level: C-MORE (cellular morphology recognition) is a workflow from bench to data analysis tailored for heterogeneous primary cells using our new R-package cmoRe. We demonstrate its utility in proof-of-principle applications such as modulation of canonical hypertrophy pathways and linkage of genotype-phenotypes in human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM). In our pilot study, exposure of cardiomyocytes to patients’ blood plasma prior vs. post aortic valve replacement allowed identification of a disease fingerprint and reflected partial reversibility following therapeutic intervention. In summary, C-MORE constitutes a valuable tool for cardiovascular research with possible fields of application in basic research and personalized medicine.