In this article, a Bayesian approach was employed for estimating the body growth of Chukar partridge (Alectoris chukar). Nonlinear growth models commonly used to estimate the growth curve of birds were fitted to weight-age data and estimates of model parameters and their credible intervals were obtained via a formal Bayesian framework. More specifically, the Gompertz, Brody, Logistic and von Bertalanffy growth models were fitted to weekly body weight data of 108 female and 72 male partridge chicks from hatch to 20 weeks of age. Deviance Information Criteria (DIC) and the coefficient of determination (R2) were employed as the goodness of fit for comparing the fitted models. The DIC and R2 values of the models ranged from 172.9 to 204.2 and 0.9765 to 0.9913, respectively. The von Bertalanffy model was found to provide the best fit in terms of lower DIC and higher R2 values, followed by the Gompertz model for both male and female partridge data. The Bayesian approach was found to be adequate for fitting complex nonlinear functions to weight-age data of Chukar partridges.