Respiratory disease is a complex phenotype and the diagnostic can be attributed to multiple causes including viral infection (e.g., respiratory coronavirus, bovine respiratory syncytial virus), bacterial infection (e.g., pneumonic spp.; lungworm), and vena caval thrombosis. Moreover, the impact of respiratory disease in cows varies with the stage of lactation when the disease is detected. In general, intense management practices facilitate the detection of respiratory disorders in dairy cattle herds relative to beef cattle herds. Thus, we propose that study of respiratory disease incidence in a large dairy cattle data set as paradigm to advance the knowledge on the factors influencing the incidence of this disease across cattle types. Respiratory disease information on 6,283 Holstein cows across four U.S. states and nine herds were evaluated. Two descriptors of respiratory disease were evaluated: days in milk to respiratory disease detection and the binary detection of respiratory disease. Survival analysis was used to study the days in milk-to-disease. The binary variable respiratory disease detection was analyzed using a binary logistic model. Lactation number, season, region, farm, body condition score, and milk yield level (3 levels) were included in the model as fixed explanatory effects whereas sire was considered a random effect. Incidence of respiratory disease was lower in summer relative to winter, and there was a nonsignificant trend on lactation number. Body condition score had a significant effect, with higher body condition score associated with lower incidence of respiratory disease. Farm, body condition score, and milk yield level had significant effect on the time when respiratory disease was identified. The heritability estimate for incidence of respiratory disease was 0.4, suggesting that despite the high number of potential causative agents, selection for less susceptible cattle can be an effective strategy to reduce the impact of this disease. The heritability estimate of the days in milk-to-disease was 0.13, showing that non-genetic components may play an important role on the stage of the lactation when the disease is detected. These findings contribute to an animal health project (USDA-NIFA-ILLU-538909) and a multistate project database (USDA-NIFA-AFRI-003542) for direct measures of health and fertility in cattle.