This study presents the development of simplified thermal models based on a zonal approach for household refrigerator, refrigerated display cabinet and refrigerated vehicle. By combining thermal models with microbiological models, it allows the prediction of the product temperature and microbial load evolution in a supply chain. The developed models are coupled with statistical models to take into account the variability related to the equipment operating conditions, microorganisms and product properties. The developed methodology has been applied to packed sliced ham sold in self-service. A sensitivity analysis was performed; it allows ranking the impact of different factors on the evolution of the microbial load. It was found that the thermal history of the product is the most influential factor before the initial microbial load. The "acceptance/ rejection " analysis shows that about 4 % of the products may present health risks (contamination by listeria monocytogenes more than 100 CFu.g-1, colony-forming units per gram of product) at the consumption point.