Monolayers of colloidal spheres are used as masks in nanosphere lithography (NSL) for the selective deposition of nanostructured layers. Several methods exist for the formation of self-organized particle monolayers, among which spin coating appears to be very promising. However, a spin coating process is defined by several parameters like several ramps, rotation speeds, and durations. All parameters influence the spreading and drying of the droplet containing the particles. Moreover, scientists are confronted with the formation of numerous defects in spin coated layers, limiting well-ordered areas to a few micrometers squared. So far, empiricism has mainly ruled the world of nanoparticle self-organization by spin coating, and much of the literature is experimentally based. Therefore, the development of experimental protocols to control the ordering of particles is a major goal for further progress in NSL. We applied experimental design to spin coating, to evaluate the efficiency of this method to extract and model the relationships between the experimental parameters and the degree of ordering in the particles monolayers. A set of experiments was generated by the MODDE software and applied to the spin coating of latex suspension (diameter 490 nm). We calculated the ordering by a homemade image analysis tool. The results of partial least squares (PLS) modeling show that the proposed mathematical model only fits data from strictly monolayers but is not predictive for new sets of parameters. We submitted the data to principal component analysis (PCA) that was able to explain 91% of the results when based on strictly monolayered samples. PCA shows that the ordering was positively correlated to the ramp time and negatively correlated to the first rotation speed. We obtain large defect-free domains with the best set of parameters tested in this study. This protocol leads to areas of 200 μm(2), which has never been reported so far.