Document classifiers are supervised learning models in which documents are assigned categories based on models that are trained on annotated datasets. In this paper, we use topic models to automatically assign categories to documents, which later are fed to document classification models. We perform experiments on several datasets in Vietnamese, collected from free online resources. Our method is promising and applicable to many datasets that have not been labeled