dTechnological advancements, particularly in the field of geographic information systems (GIS), have made it possible to predict the likelihood of foodborne pathogen contamination in produce production environments using geospatial models. Yet, few studies have examined the validity and robustness of such models. This study was performed to test and refine the rules associated with a previously developed geospatial model that predicts the prevalence of Listeria monocytogenes in produce farms in New York State (NYS). Produce fields for each of four enrolled produce farms were categorized into areas of high or low predicted L. monocytogenes prevalence using rules based on a field's available water storage (AWS) and its proximity to water, impervious cover, and pastures. Drag swabs (n ‫؍‬ 1,056) were collected from plots assigned to each risk category. Logistic regression, which tested the ability of each rule to accurately predict the prevalence of L. monocytogenes, validated the rules based on water and pasture. Samples collected near water (odds ratio [OR], 3.0) and pasture (OR, 2.9) showed a significantly increased likelihood of L. monocytogenes isolation compared to that for samples collected far from water and pasture. Generalized linear mixed models identified additional land cover factors associated with an increased likelihood of L. monocytogenes isolation, such as proximity to wetlands. These findings validated a subset of previously developed rules that predict L. monocytogenes prevalence in produce production environments. This suggests that GIS and geospatial models can be used to accurately predict L. monocytogenes prevalence on farms and can be used prospectively to minimize the risk of preharvest contamination of produce.F resh produce presents a unique food safety challenge due to the absence of a kill step between harvest and consumption. An increase in recalls and reported outbreaks linked to fresh produce over the past decade (1-3) have been associated with consumer avoidance of products linked to outbreaks (4, 5). This trend can negatively affect growers and the produce industry (4-6). For example, following a 2011 listeriosis outbreak in the United States associated with fresh cantaloupe (7), cantaloupe consumption dropped 53% nationwide (6). The prevention of produce contamination in production environments is therefore a concern for growers, the produce industry, and public health professionals. To develop effective prevention strategies, it is important to understand the ecological processes and environmental factors that affect foodborne pathogen prevalence in produce production environments. Technological advancements, such as geographic information systems (GIS), have the potential to drastically improve our ability to examine these processes and to develop novel tools for ensuring the safety of fresh produce.Numerous studies (8-21) have examined the ecology of foodborne pathogens in agricultural environments, and several (22-27) have used GIS and geospatial analysis. For example, Chapin...