Two mathematical models for the description of diabetic patient glucose behaviour are proposed. Unlike high order differential-equation based compartmental models, these models employ only the data typically available to a diabetic patient: the history of measured blood glucose concentrations and of insulin injections. The model structures are compared with a native benchmark (zero-order hold) model in a computer simulation. It is demonstrated that, given four daily blood glucose measurements and two daily insulin injections, a parametrized model of patient blood glucose response to insulin can provide relevant data in the estimation of a patient's future blood glucose response in terms of past blood glucose measurements and insulin injections. Parametrized model root means squared errors of glycaemic predictions for 18 simulated patients ranged from 7-22 mg dl-1, as compared with 19-42 mg dl-1 for the benchmark model.