The study of wetting properties at the micro and nanoscopic level is well suited to computational techniques due to its small length scale. The characteristics of wetting in these diminutive systems are exploited in fields ranging from microfluidics to labs-on-a-chip. With this presentation we outline our recent computational effort to expand the understanding and predictability of how fluids wet rough surfaces with length scales O(1) nanometers and below. Using grand canonical transition matrix Monte Carlo simulations we determine surface free energies which lead to spreading coefficients and prewetting saturation points for systems below and above the wetting temperature respectively. Surfaces investigated are comprised of static particles in crystalline configurations sculpted to differing degrees of roughness. Quantitative techniques measure the roughness and then compare data to models of wetting devised by Wenzel and Cassie. Both spreading coefficients and prewetting saturation data are extrapolated to better determine wetting temperatures, which are then also compared to the differing degrees of roughness.