Анотация: Metabolisable energy (ME) represents portion of energy utilized by the animal. Experiments for determination of ME require test animals, collection of samples and excreta, and determination of total energy content of used material. Therefore, ME determination can be expensive and time consuming. The aim of this study was to investigate the effect of enzymatic digestible organic matter (EDOM) and values of proximate chemical analysis on prediction of true metabolisable energy (TME) of feedstuffs for broilers. The performance of Artificial Neural Networks (ANN) was compared with the performance of second order polynomial (SOP) model, as well as with experimental data in order to develop rapid and accurate method for prediction of TME