The article discusses different types of multiple regression analysis and their applications in various fields. It covers multivariable/multiple linear regression, multivariate multiple linear regression, multinomial logistic regression, and multivariate non-linear regression. These methods are used in industries like manufacturing and medicine to improve models and theories. Multivariate multiple linear regression is more accurate than multivariable/multiple linear regression and can handle multiple variables. Multinomial logistic regression is mature and accurate, useful for solving problems with non-linearity and multiple independent variables. Multivariate non-linear regression requires advanced knowledge to be used effectively. Overall, multiple regression analysis is flexible and widely adopted in different settings.