The current results show substantial promise for a combined DFT/machine learning approach to solving the problem of designing bespoke materials for a new generation of organic devices and technologies. Here we have been able to predict the properties of nearly 1500 bilayer structures based on only 267 DFT calculations. Given that the time spent in the ML calculations is negligible compared with the DFT calculations, this represents a speed-up by a factor of about 5 relative to using DFT calculations alone. Moreover, it should now be possible to predict the properties of all 1.7 million bilayers built from the 1800 2D building blocks reported by Mounet et al. using this same model. This represents a speed-up of nearly 4 orders of magnitude.