This chapter explores the concept of primal approximation spaces and their foundational role in advancing rough set theory. By extending classical approximation spaces, we introduce primal structures and investigate their properties, including primal supra topology and primal approximation operators. Key results highlight the interplay between primal structures and rough approximations, offering novel insights into the topology of approximation spaces. Examples and theorems elucidate theoretical concepts, bridging the gap between abstract mathematical frameworks and potential applications. The novel approaches presented can be extended to applications in Super HyperTopology and Neutrosophic Super HyperTopology, underscoring the versatility of these methods in addressing real-world problems. Furthermore, this work bridges the gap between classical rough set models and advanced topological frameworks, providing a deeper understanding of their potential applications. These findings pave the way for future research in fields such as data analysis, decision-making, and computational modeling. Specifically, with a certain set 𝐴 in an approximation space (𝑾, 𝓡), and by utilizing the primal notion, the operator 𝛷𝐴(𝐵)(𝓡, 𝓟) is introduced. This operator generates an approximation supra-topological space.