The aim of this study was to examine the use of a nonlinear mixed modeling approach to growth studies of Japanese quail. Weekly BW measurements of 89 female and 89 male quail were used in the study. A well-known logistic growth function was used in the analysis. The function was expanded to include a sex effect and random bird effects in β0 and β2 parameters. Analyses were performed via SAS 9.2 software. The performance of 3 models, a fixed effects model (model 1) including only sex effect, a mixed effects model (model 2) including sex effect in β0 and β2 parameters and random bird effect in β0, and a mixed effects model (model 3) including sex and random bird effects in β0 and β2 parameters, was compared. The minimized value of -2 times the log-likelihood, Akaike information criterion, corrected version of Akaike information criterion, and Schwarz information criterion values indicated a better fit of model 3 relative to other competitive models. Furthermore, the error variance reduction in model 2 and model 3 compared with model 1 was 60 and 65%, respectively, indicating the better fit of the mixed effect models. Significant differences between sexes were also determined in β0 and β2 parameters, in which the males, on average, had lower β0 and higher β2 parameters than females.