Monitoring individual calves continuously using precision dairy technologies is rapidly becoming an important management tool on-farm for dairy calves; automated monitoring of feed intake and feeding behavior is particularly common. We present some of the technologies available, and 2 key uses of technology that show promise to refine dairy calf management through individual monitoring and decision-making that we argue will improve calf health, performance and welfare on farms. First, bovine respiratory disease complex (BRD) and diarrhea are prevalent illnesses in dairy calves that are critically important to detect early to avoid significant mortality risk. Studies in dairy cattle have shown that feeding behavior and intake change in the days before clinical signs of illness are visually detected (such as metritis, ketosis, and mastitis). Currently, treatment of sick dairy calves relies on caretaker experience to correctly visually identify signs of disease that are already present. We discuss how changes in feed intake and behavior using data from automated feeders can identify pre-clinical signs of illness in dairy calves, and how this data may also reveal the extent of treatment or recovery success. Second, data from technologies can be used to support nutritional management decisions and selection of calves from an early age. Automated feeders can be used to wean calves automatically based on their intakes of grain, rather than weaning calves at a set age. We describe the large variability in grain intakes and weaning ages when weaned using this method, and how individual characteristics may be used to identify those calves that will successfully wean early. This individualized feeding and weaning method offers the best chance of success for all calves, by allocating milk away from calves ready to wean and toward calves requiring more time on milk before weaning. Overall, the potential uses of precision technology tools are likely to become more common on farms, and consequently improve calf management strategies that affect the success of future dairy replacement animals.