This document provides an overview of multinomial regression. It begins with an agenda that includes multinomial regression, zero-inflated Poisson regression, and negative binomial regression. It then discusses multinomial regression in more detail, explaining that it is an extension of logistic regression used when the output has more than two categories. It also discusses model outputs such as iteration history, log odds ratios, and goodness of fit measures like residual deviance and AIC criterion.