Type 1 diabetes patients typically determine their bolus insulin needs using a bolus calculator which requires patient-and daytime-specific values for the carbohydrate-to-insulin-ratio (CIR) as well as for the insulin-sensitivity-factor (ISF). The strong inter-and intra-patient variability of blood glucose dynamics and the myriad of influencing disturbances makes estimating these factors a difficult task that is normally executed by skilled diabetologists using high quality data. In the scientific literature different methods have been proposed that should help medical professionals in determining reliable estimates of CIR and ISF. In this paper some of these methods are first introduced and then applied on one dataset recorded in a recent clinical trial. Their performance is then evaluated by comparing the estimates of CIR and ISF with the patient-and daytime-specific values used by the patients in the clinical trial. It was found that methods based on detailed data analysis perform especially well for predicting CIR, whereas simple rules of thumb tend to give better results for predicting ISF.