Here we introduce DeepCocrystal, a novel deep learning approach designed to learn the "supramolecular language" of co-crystallization. Supramolecular chemistry can be viewed as a language : atoms ('letters') form molecules ('words'), whose combinations give rise to supramolecular interactions ('sentences'). Building on this analogy, we extend current chemical language processing techniques -which predict molecular properties from single string representations -to predicting supramolecular interactions between pairs of molecules (i.e., co-crystallization). Fully-connected layers are then used to predict the co-crystallization output as a continuous number between 0 and 1, which can be then discretized (with a cut-off of 0.5) to perform a prediction ("negative" pair if below, and "positive" pair otherwise).