Energy storage is of critical importance in a variety of industries, nowhere more so than in automotive applications. Advanced batteries such as absorbent glass mat (AGM) are critical as both a primary and secondary source of electrification in vehicles with internal combustion engines or electric drivetrains, as well as hybrid models. Batteries are responsible for a wide range of safety, operational, and comfort features and the electrochemical nature of the product makes the manufacturing process highly complex. Ensuring newly built batteries meet label ratings and, ultimately, customer expectations is a key consideration for companies that manufacture batteries. This study researched key performance measures of new batteries and considered several models for predicting battery performance. The study ultimately recommended a best fit random forest model for predicting battery performance from manufacturing process indicators.