Phishing is an attractive methodology that is used by the attackers to steal personal data from people. Phishing websites are fraudulent web pages used for cyber thefts. They use domain names, similar to that of an original website, send mail and direct messages to lure someone in sharing personal information. Although many new anti-phishing methods are out ,still these attackers innovate new methods to target these. Therefore there is an alarming need to develop new ways to protect people from phishing. The Project uses different models of comparison in classification of phishing websites for detection and prediction using different machine learning models. The main goal of the project is to make Machine Learning Algorithm for data input and prediction and classify URL’s that are malicious . Using python packages(Fastai,Scikit,pandas,Seaborn etc.) the dataset is converted into Distribution Plots and Confusion Matrix.