Meeting rising quality standards while at the same time addressing climate challenges will make the commercial cultivation of Robusta coffee increasingly difficult. Whereas breeding new varieties may be an important part of the solution, such efforts for Robusta lag behind, with much of its genetic diversity still unexplored. By screening existing field genebanks to identify accessions with desirable traits, breeding programs can be significantly facilitated. This study quantifies the morphological diversity and agronomic potential of 70 genotypes from the INERA Coffee Collection in Yangambi, Democratic Republic of the Congo. We measured 29 traits, comprising vegetative, reproductive, tree architecture, and yield traits. Classification models were applied to establish whether these traits could accurately classify genotypes based on their background. Furthermore, the agronomic potential and green bean quality of the genotypes were studied. While significant variation in morphological traits was observed, no combination of traits could reliably predict the genetic background of different genotypes. Genotypes with promising traits for green beans were identified in both ‘Lula’ and ‘Lula’ – Wild hybrids, while promising yield traits were found in ‘Lula’ – Congolese subgroup A hybrids. Additionally, certain ‘Lula’ – Wild hybrids showed low specific leaf area and stomatal density, indicating potential fitness advantages in dry environments, warranting further study. Our findings highlight the agronomic potential of underexplored Robusta coffee genotypes from the Democratic Republic of the Congo and indicate the need for further screening to maximize their value.