Phishing attack is a simplest way to obtain sensitive information from innocent users. Aim of the phishers is to acquire critical information like username, password and bank account details. Cybersecurity persons are now looking for trustworthy and steady detection techniques for phishing websites detection. This paper deals with machine learning technology for detection of phishing URLs by extracting and analyzing various features of legitimate and phishing URLs. Decision Tree, random forest and support vector machine
algorithms are used to detect phishing websites. Aim of the paper is to detect phishing URLs as well as narrow them down to best machine learning algorithm by comparing the accuracy rate, false positive and false negative rate of each algorithm.