Tensile Membrane Structures (TMS) are rapidly gaining traction in the field of structural engineering, celebrated for their ability to span vast spaces, their lightweight, slender design, and their captivating aesthetic appeal. However, this inherent thinness comes with a challenge: these structures are highly susceptible to wind-induced aerodynamic forces, which can lead to significant out-of-plane deformations, dynamic instabilities such as flutter, and even material failure in rupture. Traditionally, the study of TMS behavior under wind loading has been dominated by Wind Tunnel Testing (WTT), a method that often falls short in capturing the finer, spatio-temporal nuances of wind flow. This research takes a bold step towards a deeper understanding by leveraging high-fidelity Large Eddy Simulation (LES) based Computational Fluid Dynamics (CFD) to analyze the wind dynamics affecting these structures. By meticulously modeling a neutrally stratified Atmospheric Boundary Layer (ABL) wind profile impacting the membrane structures, the study delves into key flow characteristics using velocity, vorticity, and pressure contours. A range of crucial parameters are investigated, including ground aerodynamic roughness height (z₀), structural rise-span ratio (f/L), and membrane prestress (N₀), across both open and closed configurations of TMS. One of the contributions of this research is the introduction of design pressure coefficients, categorized into distinct zones of the TMS surface through a sophisticated clustering algorithm. These coefficients, tailored for various parametric variations, offer valuable guidance for practical design applications. Additionally, peak factors—quantifying the random, fluctuating nature of pressure time histories—are evaluated and benchmarked against established models in literature. The resulting design values for these peak factors pave the way for more accurate estimation of peak pressure coefficients. To address the inherent randomness of wind excitation, a three-parameter auto Power Spectral Density (PSD) model is proposed. Moreover, recognizing the importance of multi-point wind excitations, the study introduces design Coherence Functions (CF) for cross-spectral density estimates, filling a critical gap in current design practices.