Phishing attacks, which target users through fraudulent websites and emails to steal critical information, continue to pose a significant danger to internet security. Traditional ways of detecting phishing websites frequently fall behind the shifting tactics used by fraudsters. Machine learning approaches are being used as a powerful tool for improving phishing detection capabilities in this kind of context. The current study investigates a novel Machine Learning Model for Detecting Phishing Websites that employ advanced algorithms and feature selection methodologies.Through a rigorous experimental approach, the study evaluates their performance using key metrics including accuracy, precision, and recall.Conversely, when the data was split 50-50, Random Forest yielded better results.

Keywords : Phishing; Classification; Decision Tree; Machine Learning; Cyber Security.