This study extends the findings of previous researchers by exploring linear models with and without gender and race indicators, and by validating the most promising models on a large, recently collected military data base. Boot size and outsole dimensions are also examined as predictors of stature. The results of the study indicate that models containing both foot length and foot breadth are significantly better than those containing only foot length. Models with race/gender indicators also perform significantly better than do models without race/gender indicators. However, the difference in performance is slight, and the availability of reliable gender and race information in most forensic situations is uncertain. Analogous results were obtained for models utilizing boot size/width and outsole length/width, and in this study these variables performed nearly as well as the foot dimensions themselves. Although the adjusted R-squared values for these models clearly reflect a strong relationship between foot/boot length and stature, individual 95 percent prediction limits for even the best models are plus or minus 86 mm (3.4 in.). This suggests that models estimating stature from foot/shoeprints may be useful in the development of subject descriptions early in a case but, because of their imprecision, may not always be helpful in excluding individual suspects from consideration. 11 references, 10 tables, and 1 figure (Author abstract)