Growth and drift of nine stonefly species, in a second-order, northeastern Oklahoma stream were elucidated from 19 and 13 months of sampling, respectively. Observed growth of each species (head-capsule width versus days) was analyzed with five different regression models. Growth patterns generally conformed to either a power curve (double log) or semilog regression. Coefficients of determination for best fit models ranged from 0.41 to 0.79 and were all highly significant. Haploperla brevis (Banks), Leuctra tenuis (Walker), and Amphinemura delosa (Ricker) exhibited univoltine, fast life cycles that were best modeled by semilog regressions. The univoltine, slow cycle of Acroneuria evoluta Klapalek showed good fit with a power curve. The univoltine, fast life cycles of Isoperla namata Frison, I. signata (Banks), Prostoia completa (Walker), and Allocapnia rickeri Ricker fit different types of regressions. Intraspecific differences in their growth curve shapes and rates were primarily attributed to temperature. Instars of Agnetina capitata (Pictet) nymphs were greatly spread over time and overlapped, making discretion of cohorts difficult. However, a semivoltine life cycle was suggested. This study suggests that growth characteristics of some stonefly species can be determined from lower sampling frequency, adequate to establish growth curve shape rather than the typical monthly increments. Comparison of significant semilog growth rates for each species corroborates the descriptive fast and slow classification. Stonefly drift density (0.1–7.5 nymphs per m3) was significantly lower than that of mayflies and Diptera and demonstrated a postsunset pulse. Multivariate regression of stonefly numbers in drift on current velocity and specific benthic densities accounted for a significant 25% of the variation in numbers drifting. Additional variation appears to be attributable to a greater degree of nymphal maturity as suggested by drift of predominantly pre-emergent nymphs.