Specifically, Developed a system that uses machine learning techniques to classify websites based on their URL. Basically, used four classifiers: the decision tree, random forest classifier, KNeighbours classifier and neural network. The classifiers were tested with a data set containing 1,353 real world URLs where each could be categorized as a legitimate site, suspicious site, or phishing site. The results of the experiments show that the classifiers were successful in distinguishing real websites from fake ones over 90% of the time.