The extreme conditions in molecular clouds within the ISM-characterized by low temperatures and pressures-limit the types of chemical reactions that can occur . Only reactions with very low (or zero) activation barriers are likely to proceed in these environments. Previously, we compiled a dataset of 136,081 potential association reactions among known interstellar molecules . Recently, we expanded this dataset by adding 17,572 reactions and used a machine learning model to estimate their energy barriers . Here we use multiple criteria to screen these reactions and identify the most promising prebiotic molecules, prioritizing those with low predicted barriers.