The equivalent T-stub technique is widely utilized as a design solution for steel bolted connections, which are otherwise complex to analyze. However, traditional standard-based methods often lack the precision required for accurate analysis, particularly when accounting for dynamic effects, such as those caused by earthquakes, leading to designs that may not be sustainable. This research addresses this issue by introducing a framework aimed at optimizing the bolt layout in a selected T-stub connection to maximize structural performance under cyclic loading, thereby enhancing sustainability. The finite element method (FEM) was employed to account for nonlinear characteristics, including the elastic-plastic behavior of steel, large deformations, and contact nonlinearities, ensuring precise analysis. The developed T-stub model was validated against experimental tests to reflect real-world behavior, utilizing ABAQUS finite element software. Optimization was conducted using a genetic algorithm (GA) implemented in the PYTHON programming language, linked to the simulation process. The results demonstrate the effectiveness of the proposed framework in significantly enhancing the structural performance of the steel T-stub connection under cyclic loading conditions without requiring additional material, thereby contributing to a more sustainable design.