Abstract: COVID-19, also known as 2019-nCoV, is no longer a pandemic, but a pandemic that has killed more than 651,247 people worldwide. COVID-19 currently has no specific treatment or cure, so living with this condition and its symptoms is unavoidable. This fact has made it increasingly difficult for the world's health care system, especially in developing lands. Despite the fact that there is no effective or proven clinical trial of an antibacterial agent, Although there is no mandatory goal of ending the COVID19 epidemic, there are options that can help reduce the burden. Data development is not only limited health care programs but also economics. Famous learning, data mining, in-depth learning, and other practical strategies are examples. Other alternatives such as the 2019-nCoV epidemiological diagnosis and prognosis will be simplified. shrink, decision tree, vector support machine, Naive Bayes, and neutral network. Prior to the creation of the models, an analysis of the coefficient of correlation between different dependent and independent variables was performed to determine the interaction potential between each dependent element and independent data. Training data collection was used to train models 80 percent of the time, and the remaining 20% was used to test models.