In this work, we‘re discussing the topic prediction of user return to website. At present, the casual and one-time users are a group that represents an idle potential for increasing the number of web site’s visits. The main goals is to determine the behaviour of the individual and then to use this findings to predict whether or not the user will return to the site or if the customer has lost interest in using the services. An important part of this work is the use of relatively large amount of data to analyze and track user behaviour while using the web site or look for similarities between the behaviour of users. Then, it is necessary to design a custom method, using existing methods for prediction of user return, the output of which will be the answer to whether the user will visit the site in the future again or not. Our method could be helpful also in the practise, as it can detect the deficiencies of web site because of what the web site loses its users, or it can find out the so-called occasional visitors who need to take another way to visit the site again.