This thesis is an investigation into the possibility of using automated milk feeders to predict disease in group housed preweaned calves. A scoping review was utilized to identify and characterize the current body of literature pertaining to this topic. This review identified thirteen studies which reported milk consumption, drinking speed, unrewarded and rewarded visits all as potential predictors of disease in preweaned calves. This review highlighted the discrepancy between studies including disease definitions and incomplete reporting of studies, which made comparison between studies difficult. As a follow up, a retrospective study was used to determine how feeding behaviours measured by automated milk feeders change in calves surrounding disease detection. Milk consumption, drinking speed, and unrewarded visits were found to significantly decrease leading up to illness detection in sick calves compared to healthy control calves. These computerized systems may provide a valuable tool for producers in disease detection of preweaned calves.