Synthetic derivatives of 1,4-benzoxazin-3-ones have been shown to possess promising antimicrobial activity, whereas their natural counterparts were found lacking in this respect. In this work, quantitative structure-activity relationships (QSAR) of natural and synthetic 1,4-benzoxazin-3-ones as antimicrobials were established. Data published in literature were curated into an extensive dataset of 111 compounds. Descriptor selection was performed by a genetic algorithm. QSAR models revealed differences in requirements for activity against fungi, gram-positive and gram-negative bacteria. Shape, VolSurf, and H-bonding property descriptors were frequently picked in all models. The models obtained for gram-positive and gram-negative bacteria showed good predictive power (Q2 Ext 0.88 and 0.85, respectively). Based on the models generated, an additional set of 1,4-benzoxazin-3-ones, for which no antimicrobial activity had been determined in literature, were evaluated in silico. Additionally, newly designed lead compounds with a 1,4-benzoxazin-3-one scaffold were generated in silico by varying the positions and combinations of substituents. Two of these were predicted to be up to 5 times more active than any of the compounds in the current dataset. The 1,4-benzoxazin-3-one scaffold was concluded to possess potential for the design of new antimicrobial compounds with potent antibacterial activity, a multitarget mode of action, and possibly reduced susceptibility to gram negatives’ efflux pumps.