Railway transportation systems play a vital role in urban development by offering efficient, cost-effective, and environmentally sustainable mobility. Selecting the most suitable railway line among alternatives involves multiple conflicting criteria such as safety, environmental impact, and economic feasibility, which makes decision-making a complex task. In such scenarios, conventional evaluation techniques may fall short in handling the uncertainty and vagueness inherent in expert judgments. To address this, the Spherical Fuzzy Soft Set model is applied as a decision-support tool. A distance-based evaluation method is employed to determine the optimal alternative by measuring its closeness to an ideal solution vector. This study demonstrates the effectiveness of SFSS in ranking railway line alternatives, providing a structured and flexible framework suitable for complex infrastructure planning. The results validate that SFSS enables more reliable decision-making in multi-attribute contexts by accounting for indeterminate and conflicting inputs.