Although the web has become part and parcel of our daily lives, it also provides anonymity for people who undertake malicious acts such as phishing. To deceive its victims, a phisher can use various methods like social engineering and creating counterfeit websites to steal personal and corporate account IDs, usernames, and passwords among others. To detect phishing websites several techniques have been proposed but phishers have come up with their ways of detecting them. Machine learning is one of the best approaches used in identifying these malicious activities because most phishing attacks have common characteristics that machine learning can recognize. In this paper, there is a comparison between distinct machine learning models for predicting phishing websites.