The scarcity of new antibiotics against drug-resistant bacteria has led to the development of inhibitors targeting specific resistance mechanisms, which aim to restore the effectiveness of existing agents. However, there are few guidelines for the optimal dosing of inhibitors. Extending the utility of mathematical modeling, which has been used as a decision support tool for antibiotic dosing regimen design, we developed a novel mathematical modeling framework to guide optimal dosing strategies for a beta-lactamase inhibitor. To illustrate our approach, MK-7655 was used in combination with imipenem against a clinical isolate of Klebsiella pneumoniae known to produce KPC-2. A theoretical concept capturing fluctuating susceptibility over time was used to define a novel pharmacodynamic index (time above instantaneous MIC [T>MIC i]). The MK-7655 concentration-dependent MIC reduction was characterized by using a modified sigmoid maximum effect (E max)-type model. Various dosing regimens of MK-7655 were simulated to achieve escalating T>MIC i values in the presence of a clinical dose of imipenem (500 mg every 6 h). The effectiveness of these dosing exposures was subsequently validated by using a hollow-fiber infection model (HFIM). An apparent trend in the bacterial response was observed in the HFIM with increasing T>MIC i values. In addition, different dosing regimens of MK-7655 achieving a similar T>MIC i(69%) resulted in comparable bacterial killing over 48 h. The proposed framework was reasonable in predicting the in vitro activity of a novel beta-lactamase inhibitor, and its utility warrants further investigations.