Large amounts of data are available for developing fertilizer recommendations. The maintenance, display, and analysis of such data sets can be time consuming and sometimes tedious. There are many steps required for development of fertilizer recommendations that can include database creation, data connection, presentation with GIS, repeatable functional contrasts (ANOVA and ANCOVA), regression analysis, and evaluation of prediction accuracy. Recent improvements in SAS provide numerous functions for routine data analyses in many ways. This presentation will show how to apply the SAS program more efficiently for developing fertilizer recommendations. It begins with data creation in Oracle, connecting database into SAS system with CONNECT, selecting variables interested using Proc SQL, resampling with MACRO, determining nitrogen amount that maximizes profit through an approximation using DO LOOPS in combination with MACRO and SQL, replacing dependent variables in Proc Mixed with MACRO buffer, and performing cross validation in Proc REG with MACRO. This series of applications can increase analyses efficiencies, maintain consistency of datasets, and reduce errors when transferring data.