In this research, the number of infarction cases in the hospital of Sagua la Grande during the period, 2018-2021, was modelled by means of the methodology of the Regressive Objective Regression (ROR), taking into account the incidence of some meteorological variables. The data were analysed using mathematical modelling, by means of the ROR methodology, with the help of the SPSS statistical package, version 19. The municipality of Sagua la Grande was found to have the highest number of myocardial infarctions, followed by the municipalities of Cifuentes, Corralillo and Quemado de Güines. January and February were the months with the highest incidence, followed by May and November. Days 3 and 6 were those with the highest incidence, with more than 15 cases, while the lowest number of heart attacks occurred on days 2, 19 and 30, with an average of 9.4 cases attended. The highest number of cases attended occurred in the hours from 5am to 7.59am, from 8am to 11am, as well as at 6pm, 9pm and 11pm. The average number of cases attended was 11.2/hour. The highest number of infarction victims was in the 68-73 age group, with an average of 5.1 cases. The male sex was the most affected (63.92%), while the female sex was 36.08%. In the case of the climatic variables, the minimum temperature regressed in 4 cases, the mean relative humidity regressed in 2 steps, and rainfall one step back were significant. It is concluded that, the older the age, the greater the possibility of being infarcted, where the tendency of infarcts is to occur in the morning hours, so it is possible to predict acute myocardial infarction using the ROR methodology.