Allosteric transcription factors (aTF) regulate gene expression by interactingwith target effector molecules. The specificity of aTF towards their effectors can be used for biosensing purposes. Combining them with in-vitro tools such as cell-free systems can create rapid, portable, low-cost, highly sensitive biosensors. These biosensors can be deployed to target analytes such as heavy metal ions in water supplies in places that do not possess capabilities for operating costly biosensors. To this end, we constructed a cell-free biosensor capable of sensing copper in samples like wastewater, drinking water, and biological samples. The sensor element was an aTF CueR from the MerR family of transcriptional activators capable of sensing copper. A computational model based on ordinary differential equations was constructed to simulate the transcription-translation dynamics of the sensor circuit. The overall goal of the model was to explain the copper sensing by CueR aTF. Model parameters were either estimated from literature values or experimental measurements of the concentrations of mRNA and proteins of individual species in the circuit. Unknown model parameters were estimated by minimizing the difference between model simulations and the experimental data generated from this study. In conclusion, we constructed a metal ion sensor circuit based on the CueR transcription factor and a mathematical model to optimize circuit performance. A quantitative model to predict the biosensing of metal ions like copper could be used as a starting point to simulate sensor performance for copper and other ions that are detectable via the MerR family of transcription factors.