Bayesian networks are a type of probabilistic graphical model composed of direct nodes and edges. It is a form of probabilistic graphical model. The model shows the dependencies between the variables. One of the examples of the model can be the representation of diseases and symptoms. If the symptoms are available in the individual, the individual can use the tool to understand the likelihood of various diseases. Bayesian networks should be converted into splice trees for inference as this helps in the universal application of the algorithm without any directional constraints.