In this talk, we present Dualization.jl, an extension that allows users to dualize optimization problems defined in JuMP. The dual formulation can be used to better suit the description of the optimization problem to the format expected by the conic solver. Moreover, automatic dualization can be used to model bilevel problems by automatically building some of the KKT conditions.