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Brushed 304 stainless steels (SS) are finding increasing applications in the appliances industry for their superior surface and aesthetic appearance. However, press forming 304 grade SS is still a challenge because of higher springback. This makes tooling design/ manufacturing all the more complex and iterative. This paper describes a predictive methodology to accurately simulate springback after forming and also presents experimental validation. Forming strain rates are typically higher than those encountered during normal material properties testing. Stainless steels exhibit increased elastic energy storage at higher strain rates. Since springback is essentially an elastic energy unloading process, the study shows the influence of strain rate properties for accurate springback prediction. Commercially available explicit FE code, LS-Dyna is used for predictive modeling. As an example, study on springback of 304 brushed SS during press forming on a U channel draw- bend hat section is demonstrated. Four sets of experiments on springback are carried out using different combinations of punch and die radii. For numerical experimentation, one set of experimental results is used to quantitatively assess and optimize the factors affecting the accuracy of springback prediction. The optimized set of parameters is used for springback prediction on the remaining sets. The prediction results correlate well with experiments. © 2004 American Institute of Physics [ABSTRACT FROM AUTHOR]