Optimal reliability allocation is a critical problem with applications in various fields, from engineering to software and system design. This mathematical problem involves assigning reliability values to subsystems and elements within a system, considering factors like complexity, criticality, cost, and achievable reliability. The goal is to achieve a target reliability level while minimizing costs or, conversely, to maximize reliability within budget constraints. This problem is prevalent in the design of complex software, computer systems, and mechanical or electrical systems. Previous studies have explored these allocation problems, resulting in models that allocate reliability based on the cost of increasing it. Costlier components receive lower increases in reliability. This approach can be applied to various system types, even those with a mix of failure distributions among components. However, challenges arise when complex systems require analytical reliability equations and cost functions for components, making the process time-consuming. This paper presents a model that addresses these challenges by allowing engineers to modify cost function parameters, enabling the exploration of different allocation scenarios. Engineers can then plan how to achieve the required reliabilities for each component efficiently