Diabetes is a globally prevalent disease with negative physical and economic consequences if not properly managed with medication and a balanced diet. Despite the increase in diabetes cases in recent decades, a culture of self-care has not yet been established in society. The aim of this study is to assess glycaemic behaviour using an Analytical Hierarchy Process (AHP) with metrics that assess glycaemic variability, such as Mean Amplitude of Glycaemic Excursions (MAGE), Mean Daily Differences (MODD), Continuous Overlay Glycaemic Action (CONGA) and Standard Deviation (SD), implementing data from continuous glucose monitors to generate an index called IGU, which assigns values from 0 to 10, where 0 corresponds to the best value and gradually increases up to 10, which is the worst value that can be assigned to an evaluated glycaemic profile. It has been observed that patients with diabetes have IGU values higher than 5, while patients who control the disease have values lower than 5. It can be concluded that the use of different metrics to evaluate glycaemic profiles provides a better evaluation than a single biased result.