Feed efficiency related traits modelled as repeated measurements may allow an increased precision of genetic parameters estimates, accuracy of selection and a subsequent increase in genetic gain. The objective of the present work was to compare different models for live weight (LW) and daily feed intake (DFI) during a 78-day feedlot test period using 1763 Angus Steers from the Australian Beef Information Nucleus (BIN). Genetic parameters were estimated using repeatability and random regression models for single and multiple traits. Using the bivariate random regression model, the heritabilities for LW and DFI were in the range of 0.46 to 0.56, and from 0.43 to 0.48, respectively; with repeatabilities ranging from 0.92 to 0.95, and from 0.69 to 0.72, respectively. The corresponding genetic correlation increased from 0.50 at day 1 up to 0.85 at day 78. Based on the Akaike’s information criterion and Bayesian information criterion values, random regression models presented smaller values indicating the best fit in comparison to the repeatability models. In practice, random regression analysis should be adopted for predicting more precisely the genetic merit in feed efficiency related traits. A positive and unfavourable genetic correlation was estimated for the studied traits, suggesting that it would be necessary to build a selection index to optimally select for both traits.