The integrity of the supply chain of fruits and vegetables is important to public health and well-being. With expanding global trade, the issue of unsafe imported foods has become more acute and fresh produce remains a top food category for both number of foodborne illnesses and outbreaks. Prevalence of pathogens in the production environment, risks during harvest, cross-contamination in handling, and temperature fluctuations all suggest an opportunity for tracing the cumulative effects of these events on microorganisms on products from farm to retail. The goal was to demonstrate and describe microbial dynamics in the postharvest supply chain of fresh tomatoes. An observational study was conducted on tomatoes sampled from four locations of the postharvest supply chain from Mexico to USA and analyzed individually for microbial populations: aerobic mesophiles (APC), total coliforms (TC), generic Escherichia coli (EC), and yeasts/molds (YM). APC differed (p<0.05) from 1.9±1.1, 1.7±1.1, 2.3±1.1 and 3.5±1.4 log CFU/g at postharvest, packing, distribution and supermarket, respectively. TC was <1 log CFU/g at postharvest, increased at packing (0.7±1.0 log CFU/g), decreased in distribution (0.4±0.8 log CFU/g) and increased in supermarkets (1.4±1.5 log CFU/g). Generic E. coli was not identified from TC in this supply chain. YM remained <1 log CFU/g, with the exception of 1.1±1.3 log CFU/g at supermarkets and tomatoes were not visibly spoiled. Next, to describe how and why the populations changed, the same microbial count data were used in mixed linear and logistic regression models to determine significant factors for concentration and prevalence, respectively. Location explained prevalence changes in TC and YM (p<0.05), while days-in-transit best explained concentration dynamics in all populations (p<0.05), with each additional day contributing 0.4-0.5 log CFU/g. Models illustrated supply chain microbial dynamics as certain locations increased or decreased prevalence and concentration depending on day and microorganism. With this, the Produce Supply Chain with Microbial Travelers, a modeling tool and graphical user interface, was developed to explore the relative impact of different contamination scenarios and intervention strategies on microbial behavior in the fresh tomato supply chain. These results provide data and a model framework which may be useful for future risk assessments.