We describe a morphometric technique for distinguishing the sexes of loggerhead shrikes (Lanius ludovicianus) in California, USA. We used standard morphometric measurements, as well as additional quantitative or qualitative assessments of the pattern of color on the sixth primary flight feather (P6). We reduced subjectivity in these qualitative assessments by asking six independent observers to score P6 photos of each shrike. We then developed and compared discriminant functions and multiple logistic regression models from 54 shrikes sexed by deoxyribonucleic acid. Our best models included the extent of white coloration on the primaries, tail length, bill depth, and quantitative or qualitative measurements of the angle of the black/white color transition on P6. On the basis of jackknife cross-validation procedures, our best models accurately predicted sex 86–88% of the time, despite the age and geographic variation inherent in our sample. Our results suggest that these, and potentially other, quantitative or qualitative metrics can enhance the performance of multivariate predictive models of sex identification. Furthermore, we proffer our independent observer approach as a viable means for reducing subjectivity and potential biases in the assignment and measurement of character states.