The objective of this research was to model a series of data about the number of people with cholera in six People councils of Caibarién municipality, corresponding to years 2013 and 2014. Also, to determine which model best explains the variance of this disease. The Regressive Objective Regression Methodology was used with two alternatives: the first corresponds to the use of a short-term modeling (model1) and the second, based on a modeling with climatic variables only. It was obtained that model 1 presents minor errors and explained variance, greater than model 2. The tendency of the series in the Popular Council 1 was not of significant increase, Humidity and Precipitation were not significant. A 4-month regressive parameter on the impact of cholera is presented, which coincides with previous work on acute respiratory infections. In relation to cholera trend, this variable has a 4-month regressive parameter, which coincides with the impact of El Niño phenomenon. It is concluded that model 1 is the one with the best results with the least errors and the highest explained variance and statistical regularity is the philosophical principle on which the regressive methodology is based.
