Bovine Respiratory Disease (BRD) is one of the most significant health problems in the feedlot industry. The overall objective of this project was to improve BRD detection and diagnosis in commercial feedlots using technology. The first study aimed to: (i) describe changes in body temperature, physical activity, drinking and feeding behaviours associated with BRD; (ii) compare the diagnostic accuracy of these changes for the detection of cattle with BRD: and, (iii) define the diagnostic accuracy of several combinations of physiological and behavioural parameters for the detection of BRD. By equipping 561 feedlot steers with multiple health-monitoring systems, we showed that cattle with BRD displayed a significant increase in rumen temperature, decrease in number of steps taken per day, and decrease in frequency and duration of feedbunk visits compared to healthy pen-mates. These changes were detected up to 7 days prior to clinical illness detected by pen checkers. The comparison of the diagnostic accuracy for BRD detection of these changes revealed that the most accurate were an increased rumen temperature, a decreased number of steps taken per day, and a decreased number of feedbunk visits per day. The combination in series (i.e., “and” rule) of an increased rumen temperature and a decreased number of feedbunk visits per day increased the specificity (Sp) of BRD detection up to 100% without decreasing the sensitivity (Se = 84%). The second study aimed to: (i) determine the level of agreement between a Computer Aided Lung Auscultation (CALA) system and lung auscultation by an experienced veterinarian; and, (ii) evaluate the diagnostic accuracy of CALA to diagnose BRD in feedlot cattle. Of the 561 steers, 35 were identified with visual BRD signs and 35 were selected as healthy controls. Comparison of veterinary auscultation and CALA revealed a substantial agreement (kappa = 0.77). Using latent class analysis, CALA had a relatively high Se (Se = 92.9%; 95% credible interval [CI] = 0.71-0.99) and Sp (89.6%; 95% CI = 0.64-0.99) for diagnosing BRD compared to pen checking. In conclusion, the use of health monitoring and CALA systems can improve BRD detection and diagnosis in feedlot cattle, respectively.