Well-designed environmental monitoring programs for Listeria as a strategy to identify and eliminate Listeria monocytogenes risks are essential for the produce industry and are increasingly mandated by both regulatory agencies and buyers. Along with this, industry needs science-based tools to implement responses to Listeria detection that are both appropriate for a specific facility and its unique processes and effective in reducing risk of contaminated products. As it is not practical to test out different corrective actions and sampling strategies in a given facility, our objective is to use computer modeling to identify the optimal approaches for a particular setting. Specifically, a model we have previously developed will be adapted to fresh produce processing facilities and validated with sampling data collected through an on-going project. Simulations with validated models will characterize various corrective action and monitoring schemes for their ability to detect and control Listeria in the unique settings of different facilities. As a result, the project will provide industry with science-based resources for selecting appropriate corrective action approaches and demonstrating the equivalency of different sampling strategies in their unique facilities.