The manufacturing of optical components, such as lenses or mirrors, consists of numeroussteps that are essential to the performance of the fnished optical system, such as the specifcation ofthe optical surface. For a longer period, the main focus has been in identifying and restricting thenegative effects of the low and high spatial frequency content of the surface. However, as technologyand optical equipment has become more advanced, the effects of the mid-spatial frequencies havebeen studied more, and continue to be a topic of research. As of now, there is still a need for methodsthat accurately predict and analyse the regime of mid-spatial frequencies, such that they can becontrolled during the specifcation phase, successfully limiting the need of post-processing steps.This work introduces a software tool, specifcally designed to approach this problem, which wasto be developed in Python as a contribution to the existing Optical Scripting Library at OHB. Byspecifying an optical component in terms of a Power Spectral Density function, together with thecontributions from different spatial frequency domains and the application of a ripple patterns, thissoftware tool can generate pseudo-random optical surfaces, which maintains the input specifcations.Furthermore, a Dynamic Link Library fle was developed, sharing the same functionality as thePython implementation, allowing for simulations using Zemax OpticStudio. Using the software tool,it was found that the relative error between input and output measurements were approximately0.78%, in terms of the Power Spectral Density Function. In addition, the result of analysing one of thetwo test cases indicate that the software tool is effective in predicting the infuence of mid-spatialfrequency errors, fulflling a previously measured predicition. The second test case proved that thesoftware tool can be used for mimicing surfaces of real measurements, holding the same specifcations.