Natividad Gómez, PatriciaOtiniano Quispe, MiltonNatividad Gómez, Patricia2021-08-172022-02-222021-08-172022-02-222021-07978-958-52071-8-92414-6390http://laccei.org/LACCEI2021-VirtualEdition/meta/FP303.htmlhttp://dx.doi.org/10.18687/LACCEI2021.1.1.303https://axces.info/handle/10.18687/20210101_303The objective of this article is to achieve a statistical analysis of the data from the World Happiness Report and its relationship with the economic income of the countries, as well as to identify that variables other than the economic one (GDP) affect happiness. The approach uses research methodology, and uses Machine Learning techniques to generate models that represent the function to predict the happiness score or category of a country, as well as a hypothesis test. The results determine that there is a positive relationship between economic income and happiness, but up to a certain level the relationship is marginal, and that there are other aspects such as those related to social factors that are decisive to establish the degree of happiness in a country.EnglishLACCEI Licensehttps://laccei.org/blog/copyright-laccei-papers/HappinessWorld Happiness ReportGDPCountry economyPythonMachine learningArticle