Simple SummaryPrediction equations allow small farmers who do not have a scale to estimate the live weight of animals from their body measurements. The aim of this study was to describe the morphology and estimate the live weight from body measurements of Socorro Island Merino lambs. A group of Socorro Island Merino lambs was recorded from birth to year for live weight, rump width, rump length, withers height, body length, cannon bone perimeter, and chest girth, width, and depth. Sex and crossbreeding with hair breeds affected weight and mainly thoracic morphology at birth and at the year of Socorro Island Merino lambs, with the greatest and smaller weights and body measurements being observed in crossbreed males and purebred females, respectively. The highly significant and positive correlation between LW and CG suggests that this variable can be used as the sole predictor in exponential and linear models and in combination with other measurements in multiple linear models to provide a good estimate of LW. Chest measurements could be used as an indirect selection criterion to improve growth traits in this breed.AbstractThe aim of this study was to describe the morphology and estimate live weight from body measurements of Socorro Island Merino lambs. A group of Socorro Island Merino lambs was recorded from birth to year for live weight, rump width, rump length, withers height, body length, cannon bone perimeter, and chest girth, width, and depth. The effect of the lamb type on body measurements and live weight was analyzed using ANOVA, Pearson’s correlation analysis was performed to estimate the relationship between body measurements and live weight, multiple linear regressions were fitted to obtain prediction equations of live weight from the body measurements and finally, chest girth was used to generate prediction equations using linear and exponential models. At birth and at year, differences were observed in body measurements, especially those related to the thoracic region, with crossbred males showing the highest values. Live weight was correlated with almost all the body measurements, with the highest coefficients observed with chest girth, chest width, and chest depth. Live weight can be accurately predicted from multiple regression equations using several body measurements, but using only chest girth (CG) as a predictor, the exponential equation W0–365= 0.9142 exp(0.0462 CG)showed the best accuracy.