This paper considers approaches to modeling the dynamics of infectious disease and the application of such models to nematode parasite infections in ruminants. Particularly, these models are developed to account for host genetics and may be used to assess the effects of using genetics to control nematode infections. Three main issues are critically examined: the infection transmission cycle from pasture to host to pasture, the expected genetic relationships between resistance and performance, and the risks of parasite evolution in response to genetic changes in the host. To obtain answers that are realistic and of practical use, the modeling approaches require a solid grounding in biology. This biology is formalized and described using mathematical techniques, with the models parameterized using experimental or field data. Transmission dynamics have been quantified by modeling and are backed by strong experimental data. Selection for resistance will be successful in reducing egg output, pasture larval contamination and hence subsequent larval challenge. Modeling frameworks have been developed to predict genetic relationships between resistance to infectious disease and performance in general, and genetic correlations predicted for nematode resistance are close to mean published values. These predicted correlations strengthen as the larval challenge increases and the dietary (protein) adequacy decreases, however modeling challenges remain. Lastly, although convincing experimental data is not yet available, arguments based on modeling suggest that the risks of parasite evolution in response to genetic changes in the host should be less than the risks arising from other control strategies, such as anthelmintics. Thus, modeling techniques predict that selective breeding for resistance should be an effective and sustainable complementary control measure.