Deadlock represents a critical threat in operating system resource management, as it has the potential to bring all computational processes to a complete halt. This study examines the effectiveness, efficiency, and constraints of the Banker's Algorithm as a deadlock avoidance mechanism through a multi-scenario quantitative simulation. The data were derived from simulations involving three core components: the resource allocation matrix (Allocation), the maximum process requirement declaration (Max), and the resource availability vector (Available), within a system configuration consisting of five processes and three resource types. The findings demonstrate that the Banker’s Algorithm accurately distinguishes between safe and unsafe states through its two primary mechanisms: the Safety Algorithm and the Resource-Request Algorithm. With Available set to [3, 3, 2], the algorithm successfully identified the safe execution sequence ⟨P1, P3, P4, P0, P2⟩, ensuring all processes could complete without deadlock risk. When Available was reduced to [2, 1, 0], the system entered an unsafe state in which no process could initiate execution. Through multi-scenario simulations, the critical transition threshold from a safe to an unsafe state was identified at approximately 83% resource utilization. In terms of efficiency, the O(n²×m) time complexity makes the algorithm well-suited for small to medium-scale systems, though it may become a performance bottleneck in large-scale cloud computing environments. This study produces a quantitative evaluation framework that can serve as a reference for implementing the Banker’s Algorithm in modern operating systems.