In this article, I introduce new commands to estimate text regressions for continuous, binary, and categorical variables based on text strings. The command txtreg_train automatically handles text cleaning, tokenization, model training, and cross-validation for lasso, ridge, elastic-net, and regularized logistic regressions. The txtreg_predict command obtains the predictions from the trained text regression model. Furthermore, the txtreg_analyze command facilitates the analysis of the coefficients of the text regression model. Together, these commands provide a convenient toolbox for researchers to train text regressions. They also allow sharing of pretrained text regression models with other researchers.