Bayesian Networks are becoming an increasingly important area for research and application in the entire field of Artificial Intelligence. This paper explores the nature and implications for Bayesian Networks beginning with an n overview and comparison of inferential statistics and Bayesâ„¢ theorem. The nature, relevance and applicability for Bayesian Network theories for advanced computability form the core of the current discussion. A number of current applications using Bayesian networks are examined. The paper concludes with a brief description of the appropriateness and limitations of Bayesian networks for human-computer interactions and automated learning.