This project investigates the integration of machine learning-driven predictive maintenance into the Mobile Wings system, which is meant to care for Cockatiels (Cockatiels), to increase system dependability and user happiness. A predictive maintenance model was created utilizing Random Forest, SVM, and Neural Networks, which were trained on Mobile Wings sensor data. Following integration, the system had a 67% reduction in average downtime (from 15 to 5 h per month) and boosted system uptime from 85% to 95%. Maintenance frequency was reduced from 10 to 4 times per month, and user satisfaction rose from 3.8 to 4.5 on a 5-point scale. The study shows that predictive maintenance improves system performance and reliability, with important implications for automated care systems.