When trying to explain something as complex as the Bayes theorem, it's rather hard to do it justice. This theorem, even though it is simple in theory, has a rather huge and complex application throughout different industrial, statisthical, economical and business enterprises and institutions. It's hard to really shine a light on the full spectrum of it's possibilities. However, the goal was to make a short and intuitive compedium of the basics of the Bayes theorem and it's application. Starting off with the definition of the theorem and it's basic characteristics, we advance to the implementation of the theorem in the simplest of problems. Starting with the simple problems, such as pulling a vanilla cookie from random bowls, the identical twin of Elvis and others , we try to explain the basics of the Bayesian statistics and it's theorem. Throughout the compedium, we shall go over the more complicated problems where we shall display how using the entire theory of probability and the Bayesian theorem has a significant role in every day tasks and more complex issues. Problems such as Oliver's blood, german tanks and Monty Hall, are just some of the often and real issues that can be solved using the theory of probability. Since it is impossible to showcase the full potential of the Bayesian statistics and it's theorem we will showcase a short overview into the more advanced and really complex capabilities and applications of the theorem when dealing with multidimensional problems. Those who want to know more, can find references and literature in the appropriate section.