Bacteria modify their morphology in response to various factors including growth stage, nutrient availability, predation, motility and long-term survival strategies. Morphological changes may also be associated with specific physiological phenotypes such as the formation of dormant or persister cells in a “viable but non-culturable” (VBNC) state which frequently display different shapes and size compared to their active counterparts. Such dormancy phenotypes can display various degrees of tolerance to antibiotics and therefore a detailed understanding of these phenotypes is crucial for combatting chronic infections and associated diseases. Cell shape and size are therefore more than simple phenotypic characteristics; they are important physiological properties for understanding bacterial life-strategies and pathologies. However, quantitative studies on the changes to cell morphologies during bacterial growth, persister cell formation and the VBNC state are few and severely constrained by current limitations in the most used investigative techniques of flow cytometry (FC) and light or electron microscopy. In this study, we applied high-throughput Imaging Flow Cytometry (IFC) to characterise and quantify, at single-cell level and over time, the phenotypic heterogeneity and morphological changes in cultured populations of four bacterial species, Bacillus subtilis, Lactiplantibacillus plantarum, Pediococcus acidilactici and Escherichia coli. Morphologies in relation to growth stage and stress responses, cell integrity and metabolic activity were analysed. Additionally, we were able to identify and morphologically classify dormant cell phenotypes such as VBNC cells and monitor the resuscitation of persister cells in Escherichia coli following antibiotic treatment. We therefore demonstrate that IFC, with its high-throughput data collection and image capture capabilities, provides a platform by which a detailed understanding of changes in bacterial phenotypes and their physiological implications may be accurately monitored and quantified, leading to a better understanding of the role of phenotypic heterogeneity in the dynamic microbiome.