  Phishing emails continue to pose a significant threat, causing financial
losses and security breaches. This study addresses limitations in existing
research, such as reliance on proprietary datasets and lack of real-world
application, by proposing a high-performance machine learning model for email
classification. Utilizing a comprehensive and largest available public dataset,
the model achieves a f1 score of 0.99 and is designed for deployment within
relevant applications. Additionally, Explainable AI (XAI) is integrated to
enhance user trust. This research offers a practical and highly accurate
solution, contributing to the fight against phishing by empowering users with a
real-time web-based application for phishing email detection.
