The Kaiser–Meyer–Olkin (KMO) value (0.892) and Bartlett’s test confirmed that the data were suitable for factor analysis. Principal component analysis (PCA) identified two principal components that together explained 79.67 % of the total variance and represented the spine/back and pelvis/lower-body regions. Positive phenotypic correlations, indicating coordinated variation among traits, supported the use of PCA to summarize body condition in Anatolian cattle.