Diabetes is increasing at an alarming rate in the US. According to the CDC, the number of cases has risen to an estimated 34.2 million in 2020. Therefore, there is a pressing need for rapid and robust detection of blood glucose levels. Recent advancements in synthetic biology, particularly in cell-free bio-sensing, address this need. Cell-free biosensors provide direct access to the translation machinery thereby promoting enhanced sensitivity and reduced response times. To improve upon existing technology and provide an alternative testing methodology, we propose a glucose biosensor with synthetic regulatory elements for rapid point-of-care (POC) detection of glucose. In this study, we investigated the design of a transcription factor-based cell-free biosensor and developed a mechanistic model to simulate its response to varying blood glucose levels. Model performance was qualitatively examined through simulations, followed by quantitative validation against experimental measurements. The subsections of the regulatory network were treated as individual cell-free circuits for model validation. Unknown parameters were estimated using multi-objective optimization and an ensemble modeling approach was used to account for uncertainty in the estimates. Finally, for a detailed analysis of the influence of model parameters on expression dynamics, we performed global sensitivity analysis. Taken together, the modeling approach successfully captured the expression dynamics of individual components of the biosensor. This work paves the way for the development of portable diagnostic technologies which are user-friendly, rapid, and robust, thus holding great potential to deliver POC treatment to resource-limited settings. Ultimately, this framework can be extended to serve as a potential platform for insulin delivery.