ChemML is a machine learning Python package for the analysis and modeling of chemical and materials data. We have been pursuing initial steps to integrate the ChemML package into the OpenChemistry platform. In addition to adding ML functionality to OpenChemistry, we aim to make these techniques more accessible and advance their broader dissemination in the chemistry community. The focus of the current work has been to compile a collection of trained ML prediction models for certain materials properties that can be used as alternatives to corresponding physics-based modeling or simulation approaches. As proof of principle, we designed and implemented a deep learning model for the prediction of the refractive index values of organic compounds.