Throughout history, people’s health has been linked to internal and external factors that influence their socio-economic environment. A clear example is breast cancer, which has its origins in risk factors related to physical inactivity, weight gain and alcohol consumption, among others. The majority of predicted cases are female and a small proportion are male. The penetration of technology in most sciences and fields of work has increased the positive progress in solving complex problems. Big data applied to health allows the discovery of relevant information derived from data related to diseases, prognoses and treatments. The main objective of this research is to determine the diagnosis of breast cancer based on the results of classification models applied to genomic data. The research methodology will be quantitative, with measurable and verifiable results. The development methodology used is a modification of the incremental methodology, with flexible steps to verify and modify the results obtained in each activity. The experimentation tool used is RStudio together with the R programming language.