This paper proposes to extend a previous work, "The Effect of the Back Button in a Random Walk: Application for PageRank". We introduce an enhanced version of the PageRank algorithm using a realistic model for the Back button, thus improving the random surfer model. We show that in the special case where the history is bound to an unique page (you cannot use the Back button twice in a row), we can produce an algorithm that does not need much more resources than a standard PageRank. This algorithm, BackRank, can converge up to 30% faster than a standard PageRank and suppress most of the drawbacks induced by the existence of pages without links.