Background: Visual tracking of object is one of the dominant fields in image processing sector and it is the primary resource which is being used to ensure the safety of various networks and processes which involve movement of objects.Object tracking has numerous real-world applications for example computerized surveillance scheme, military management, transportation administration system, crime recognition system, artificial intelligence and robot vision system. Bayesian theorem has a very significant role to play in evaluation of various processes and techniques. Methods: This paper deals with the evolution of application of Bayesian theorem and proposes moving objects tracking process depended on the Kalman filter.The procedure is framed in two steps to recursively obtain a linear solution with optimal filtering. Result and discussion: The tracking of a moving object is implemented using a simulation tool. The results analysed using Matlab reveals the fact that the efficiency of the suggested system is applicable for moving objects stalking in real-time. Conclusion: Bayesian indicators are the reason of coherent inference in the existence of uncertainty. It is an appreciated logical resource, bringing transparency to the formulation and analysis of many baffling problems.