The development of relevant predictive models for single-cell lag time and growth probability near growth Limits is of critical importance for predicting pathogen behavior in foods. The classical methods for data acquisition in this field are based on turbidity measurements of culture media in microplate wells inoculated with approximately one bacterial cell per well. Yet, these methods are labour intensive and would benefit from higher throughput. In this study, we developed a quantitative experimental method using automated microscopy to determine the single-cell growth probability and lag time. The developed method consists of the use of direct cell observation with phase-contrast microscopy equipped with a 100× objective and a high-resolution device camera. The method is not a time-lapse method but is based on the observation of high numbers of colonies for a given time. Automation of image acquisition and image analysis was used to reach a high throughput. The singlecell growth probabilities and lag times of four strains of Listeria monocytogenes were determined at 4 ◦C. The microscopic method was shown to be a promising method for the determination of individual lag times and growth probability at the single-cell level.