Animal health plays a critical role in ensuring food safety, farm productivity, and economic sustainability in the livestocksector. Early detection of health issues is vital for preventing the spread of disease and minimizing losses. This project proposes thedevelopment of a Smart Animal Temperature Monitoring and Disease Detection System that enables real-time tracking of ananimal's body temperature and health condition through a combination of IoT technology and data analytics.The system employs wearable temperature sensors attached to each animal, which continuously monitor body temperature andtransmit data to a centralized platform. This data is analyzed using predefined thresholds and machine learning algorithms to detectearly signs of fever and other temperature-related anomalies, which are often the first indicators of disease. In case of abnormalreadings, instant notifications and alerts are sent to the livestock owner or caretaker via a mobile and web application, allowing fortimely intervention.In addition to temperature monitoring, the system aims to incorporate behavior-based analysis and environmental data integrationto enhance disease prediction accuracy. The application provides a user-friendly dashboard for monitoring individual and herdhealth status, historical data trends, and automatic health reports, supporting better decision-making in animal care.This intelligent solution not only promotes proactive health management but also reduces veterinary costs, enhances productivity,and supports animal welfare. The system is scalable, adaptable across various types of livestock, and provides a modern, data-drivenapproach to disease prevention in animal husbandry