The objective of this study was to determine the relationship of body linear measurements such as hip height (HH), girth circumference (GC), point of the shoulder to hip length (HipShL), forearm circumference (FntLC) and BW with real-time ultrasound (RTU) measurements of body composition, in Boer × Spanish cross yearling goats (n = 90; n = 48 wethers and n = 42 doelings). The body composition traits measured by RTU were 12–13th rib longissimus lumborum muscle area (uLMA), 12–13th rib fat thickness (uBF), and rump fat thickness (uRUMP). Ultrasound measurements were taken using an Aloka 500 with a 12 cm 3.5 MHz transducer, hair was clipped and vegetable oil was used as a coupling agent to enhance image quality. Data were analyzed by gender and also pooled using the Proc CORR and Proc REG procedures of SAS. BW was highly correlated (P < 0.0001) to HH, GC, HipShL, FntLC, uLEA, uBF, and uRUMP (0.65, 0.85, 0.62, 0.70, 0.89, 0.75, and 0.70, respectively) with the pooled data. Similar results were observed when data were analyzed by gender. However, a lower correlation was observed between BW and HIpShL and FntLC with the doelings (0.46 and 0.48, respectively) and between BW and HH, uBF and uRUMP for the wethers (0.35, 0.38, and 0.36, respectively). Prediction equations were also developed to predict uLEA, and uBF. Predictions of uLEA had an R² of 0.75, 0.64, and 0.65 for the pooled, wether and doelings data, respectively, with BW and HipShL included in the pooled and doelings model and BW and FntLC in the wether model. Predicitons of uBF had an R² of 0.59, 0.23, and 0.68 for the pooled, wether and doelings data, respectively, with BW and HipShl included in the pooled and wether models and BW and HH in the doeling model. Results showed that RTU body composition traits are highly correlated to body linear measurements in yearling Boer × Spanish yearling goats and that different measurements within gender accounted for more variation within the RTU traits. More research is needed to refine the models and improve accuracy of prediction.