Antibiotic resistance is a critical global public health challenge driven by the limited discovery of antibiotics, the rapid evolution of resistance mechanisms, and persistent infections that compromise treatment efficacy. Combination therapies using antibiotics and nanoparticles (NPs) offer a promising solution, particularly against multidrug-resistant (MDR) bacteria. This study introduces an innovative approach to identifying synergistic drug-NP combinations with enhanced antimicrobial activity. To carry this out, we compiled two groups of data sets to predict the minimal concentration (MC) and zone of inhibition (ZOI) of various drug-NP combinations. CatBoost regression models achieved the best 10-fold cross-validation R