Exhaled volatile organic compounds (VOCs) represent ideal biomarkers of endogenous metabolism and could be used to non-invasively measure circulating variables, including plasma glucose. We have previously demonstrated that hyperglycemia in different metabolic settings (glucose ingestion in pediatric type 1 diabetes) is paralleled by changes in exhaled ethanol, acetone and methyl nitrate. In this study we have integrated these gas changes along with 3 additional VOCs (2 forms of xylene and ethylbenzene) into multi linear regression models to predict plasma glucose profiles in 10 healthy young adults, during the 2 hours following an i.v. glucose bolus (matched samples of blood, exhaled and room air were collected at 12 separate time points). The 4-gas model with highest predictive accuracy estimated plasma glucose in each subjects with a mean "R" value of 0.91 (range 0.70-0.98); increasing the number of VOCs in the model only marginally improved predictions (average "R" with best 5-gas model = 0.93; with 6-gas model = 0.95). While practical development of this methodology into clinically usable devices will require optimization of predictive algorithms on large-scale populations, our data prove the feasibility and potential accuracy of breath-based glucose testing.