The increase of internet usage in recent times has been a noticeable change in this generation. Users from all over the world use social sites to interact across the world. Countless websites are present today. With countless networks and sites, some people or companies tend to create new ways to lure out the random users using the web, such as phishing. In phishing, the normal users are swindled to use the fraudulent websites. The aim is to identify the phishing websites with great accuracy and compare different methods by which phishing websites can be tracked in an easier and more accurate way. Comparative studies of various algorithms are tested with the help of 10,000 datasets, each tested with 18 different parameters to increase the accuracy score of each algorithm. The paper shows the methods used for phishing detection are more accurate than other practices done so far using certain appropriate parameters and more useful.