This chapter provides an overview of SAS/STAT procedures that perform regression analysis. The REG procedure provides extensive capabilities for fitting linear regression models that involve individual numeric independent variables. Many other procedures can also fit regression models, but they focus on more specialized forms of regression, such as robust regression, generalized linear regression, nonlinear regression, nonparametric regression, quantile regression, regression modeling of survey data, regression modeling of survival data, and regression modeling of transformed variables. The SAS/STAT procedures that can fit regression models include the ADAPTIVEREG, CATMOD, GAM, GENMOD, GLIMMIX, GLM, GLMSELECT, LIFEREG, LOESS, LOGISTIC, MIXED, NLIN, NLMIXED, ORTHOREG, PHREG, PLS, PROBIT, QUANTREG, QUANTSELECT, REG, ROBUSTREG, RSREG, SURVEYLOGISTIC, SURVEYPHREG, SURVEYREG, TPSPLINE, and TRANSREG procedures. Several procedures in SAS/ETS software also fit regression models.