Image-based cell profiling has become a common tool to identify phenotypic changes in cells exposed to various stimuli. To apply this approach to any research organism, we developed Image3C (Image-Cytometry Cell Classification), a tool that enables clustering of single cells based on their intrinsic phenotypic features by combining image-based flow cytometry with cell cluster analysis. We conducted a morphology analysis of hematopoietic tissue from zebrafish and a phagocytosis experiment. Here, Image3C could identify major hematopoietic cell lineages and, in addition, cells with specific functions, which abundance can be statistically compared between different treatments. To test the versatility of Image3C, we also clustered hemocytes of the apple snail Pomacea canaliculata obtaining results consistent with those collected by classical histochemical approaches. These experiments illustrate how Image3C can be used to classify and visualize heterogenous cell population obtained from either invertebrates or vertebrates without the need of antibodies or molecular databases.