A Bayesian network is a probabilistic graphical model that represents a set of variables and their conditional dependencies through directed acyclic graphs. Some other synonyms for Bayesian network include probabilistic network, belief network, graphical model, causal network, and decision network. The application of Bayesian networks is widespread in several fields, including machine learning, artificial intelligence, medicine, genetics, economics, and finance. Different variations of Bayesian networks exist, including dynamic Bayesian networks, hidden Markov models, factor graphs, and Bayesian hierarchical models. Bayesian networks are particularly useful in decision making due to their ability to handle uncertain and incomplete data. They have contributed significantly to the development of decision-making systems for diverse applications, including risk analysis, diagnosis, and prediction.