In this article, I present ivtreatreg, a command for fitting four different binary treatment models with and without heterogeneous average treatment effects under selection-on-unobservables (that is, treatment endogeneity). Depending on the model specified by the user, ivtreatreg provides consistent estimation of average treatment effects by using instrumental-variables estimators and a generalized two-step Heckman selection model. The added value of this new command is that it allows for generalization of the regression approach typically used in standard program evaluation by assuming heterogeneous response to treatment. It also serves as a sort of toolbox for conducting joint comparisons of different treatment methods, thus readily permitting checks on the robustness of results.