Transformers are essential and costly components in power systems, where failures can lead to widespread power disruptions, environmental hazards, and risks to personnel. This research focuses on improving the reliability and resilience of Bhutan's power system through effective condition monitoring and fault diagnosis of transformers. By implementing cost-effective and reliable monitoring methods from the installation stage, the study seeks to prevent major power outages that could impact Bhutanese utility operations. A comparative analysis of various condition monitoring techniques is conducted, with an emphasis on selecting the most suitable methods for Bhutan's power grid infrastructure. Additionally, the research introduces a straightforward real-time temperature prediction algorithm designed to estimate the hot-spot temperature of smaller transformers. This algorithm considers load and ambient temperature variations to provide insights into thermal behavior, allowing operators to make proactive, informed decisions. Key findings highlight the importance of predictive maintenance strategies, demonstrating that targeted monitoring can significantly enhance the lifespan and efficiency of transformers while minimizing the risk of unexpected failures.