A wide selection of lamb types (n = 360) of mixed sex (ewes and wethers) were slaughtered at a commercial abattoir. Soft tissue depth at the GR site (thickness of tissue over the 12th rib, 110 mm from the midline) was measured in the chiller, using a GR knife (GR). Each carcass was subsequently broken down to a range of trimmed boneless retail cuts and the lean meat yield determined. The predominant industry model for predicting meat yield in Australia uses hot carcass weight (HCW) and tissue depth at the GR site. A moderate level of accuracy and precision was found when HCW and GR were used to predict lean meat yield (R² = 40.5, r.s.d. = 2.39%), which could be improved markedly when loin muscle cross-sectional area at the 12th rib (EMA) was included in the model (R² = 54.5, r.s.d. = 2.10%). A better result was achieved when the model included the weight of subcutaneous fat (SLFat) from the shortloin (R² = 73.8, r.s.d. = 1.59%). A combination of SLFat and the weight of the shortloin muscle (SLMus) negated the need to include either GR or EMA in the model (R² = 76.1, r.s.d. = 1.52%). The transportability of a model based on HCW, SLFat and SLMus was tested by randomly dividing the dataset and comparing the coefficients and the level of accuracy and precision. Collecting measures of EMA, SLFat and SLMus in boning rooms is potentially feasible. If this can be achieved under commercial conditions, a rigorous method for automatically predicting lean meat yield during boning could be applied. Application of the approach to large-scale research programs, where estimates of lean meat yield are required, would be possible at a reduced cost compared with alternative systems based on full carcass breakdown. A suitable model is given for this purpose.