This study enhances uncertainty management by integrating soft set theory with neighborhood systems. Existing models use fixed relations, lacking adaptability to varying contexts. We introduce eight soft neighborhood types built from parameterized relations, generalizing existing models like Yao’s [17] and Mareay’s [12] approaches, enabling flexible approximations. By constructing topologies from these neighborhoods, we develop refined lower and upper approximation operators. This work bridges soft set parameterization with topological structures, offering a foundational framework for uncertainty management in parameter-dependent systems