Digital, computational and engineering applications use the powerful framework of discrete dynamical systems on finite state spaces to model efficiently processes with deterministic or rule based dynamics. This paper suggests a structured representation which is constituted by finite state representation, state transition functions, a mechanism for discrete time updates, and utilizes them to analyze the evolution of the system from one time instant to the next. A strategy for efficiently encoding the state is suggested that will represent finite configurations, and a design of the transition rule is suggested to provide consistent and deterministic transition of the state. Proposed framework focuses on the simplicity of the computation, its scalability and its reproducibility for finite dimensional systems. The stability of convergence is demonstrated by performance evaluation, as well as the accuracy of the state prediction; the computational complexity is low; and transition management efficiency with different starting conditions is shown. The outcome demonstrates the effectiveness of the proposed method to capture discrete dynamic behavior and suggests its potential applications in different areas like automata theory network modelling, control systems and analysis of algorithms, etc., providing a good foundation for the future continuous-time computational research.