The aim of this study was to choose the best predictive model for the accurate description of the average flock growth of laying hens and for the daily egg mass being produced by the layers during the productive period. The calculations were undertaken with the generalised data on the weight growth and daily egg mass, produced by the commercial flock of a Shaver White laying hens breed. The model, represented as the ratio of the polynomials of the third and the second powers, was deduced by the authors for the prediction of the growth and daily egg mass production curves. This Narushin-Takma model was tested for the accuracy of the results prediction in comparison with the following growth models: the logistic, the Gompertz, the von Bertalanffy, the Richards, the Weibull and the Morgan-Mercer-Flodin functions. The egg production model used for comparison were the Adams-Bell, the logistic-curvilinear, the compartmental and the Lokhorst functions. Fitting criteria were estimated as the coefficients of determination R-2 and the final loss L-f of the loss function: sum of observed minus predicted data in the second power. The Narushin-Takma model was found to be the best in description of the both curves, values for R-2 of 0.9997 and for L-f of 0.005 for the evaluation of the body growth data and values for R-2 of 0.996 and L-f of 0.001 for the description of the egg mass producing function. The accuracy of the other models was high and almost the same for all functions. The order of the accuracy for the compared models was as follows: for the body growth curve - the Weibull model, the Gompertz, the von Bertalanffy, the Morgan-Mercer-Flodin, the logistic and the Richards functions; for the egg mass producing curve - the logistic-curvilinear model, the compartmental, the Lokhorst and the Adams - Bell functions. (C) 2003 Silsoe Research Institute. All rights reserved Published by Elsevier Science Ltd.