Postprandial glycemia (PPG) is a relevant determinant of glucose control in people with type 2 diabetes (T2D). Epidemiological and pathophysiological studies indicate that PPG is a better risk predictor for cardiovascular disease and all-cause mortality than fasting plasma glucose. Therefore, both fasting and postprandial glycemia should be targeted to achieve optimal glycemic control and, thus, prevent or reduce the risk of diabetes complications. Post-prandial glucose response (PGR) cannot be predicted based solely on the meals' carbohydrate content. Recent research using continuous glucose monitoring (CGM) systems has identified different patterns of PGR to a standard meal among both healthy people and individuals with type 1 diabetes. Different contributors to the PGR have emerged, including genotype, hormonal and metabolic factors, phenotype, gut microbiota composition, background diet, sleep habits, physical activity levels. The present project aims at exploring the PGR in a real-life setting in a cohort of people with T2D, and identifying person-specific factors associated with different postprandial glucose patterns. To this purpose, 144 individuals with T2D on treatment with diet alone or diet plus metformin will be characterized for their anthropometric, metabolic, and gut-microbiome features and will undergo a one-week observational period through CGM system, while properly recording their food intake, physical activity, and sleep habits. A mixed-nutrient standardized meal will be consumed at home in two occasions by each participant to investigate the intra-individual variability of the PGR. Moreover, in a subgroup of participants (n=60), divided according to anthropometric and metabolic features, hormonal and metabolic response to the standardized meal will be evaluated at the hospital, to explore the contribution of different T2D phenotypes to the PGR. A further step will be developing a prediction algorithm of PGR based on the intra- and inter-individual factors shown to influence postprandial glucose, able to further optimize the management of T2D with precision therapeutic strategies.