A Bayesian Network is a graphical model used to visually represent connections between variables. The main task performed on a Bayesian Network is the inference of a posterior probability distribution of one or more nodes which represents the probability that each variable’s state has to occur. This probability distribution is used as a support to take decisions in the real world case which the network models. A factor to consider when taking decisions based on a posterior probability distribution is the influence that a parent node has on the node of interest. Based on the strength of influence measured, the user can alter its decision in accordance to the real world case.