The three main parameters used by patients in diabetes management are initial blood glucose, carbohydrate amount, and mealtime difference. In this study, a novel open-loop control algorithm was proposed, which aims to determine the correct value of mealtime difference duration. Unlike current blood glucose estimation methods, this algorithm was focused on determining extreme points that only concern patients such as hyperglycemia and hypoglycemia, instead of predicting all blood glucose trace in the postprandial period. This new approach has made it possible to determine extreme blood glucose values with simple linear equations without using complex models. This algorithm has only three parameters and has been validated in the UVA Padova type 1 diabetes mellitus simulator, which has thirty in-silico patients. The regressions between real and predicted values for hypoglycemia, hyperglycemia, and mean blood glucose were 0.95, 0.99, and 0.98, respectively. Using the proposed algorithm, the severity of hyperglycemia, mean blood glucose, and standard deviation values were reduced, and hypoglycemia events were prevented. Postprandial blood glucose curves have occurred as desired and within normal limits. Furthermore, it was concluded that intersection points of blood glucose curves contain information about the metabolic parameters of the patients, in this study.