Logistic regression was applied to develop a morphometric sexing method of two closely related stork species that were previously sexed through amplification of the CHD gene. Tarsus length (TL) and bill length (BL) measurements were recorded from captive populations of adult Milky Stork (Mycteria cinerea) (n = 60) and Painted Stork (Mycteria leucocephala) (n = 58) at Zoo Negara Malaysia. Despite having monomorphic plumages, both stork species exhibited normal sexual size dimorphism in which males were significantly larger than females in the tested variables. Based on logistic regression analysis, BL correctly classified the sex of sampled individuals from Painted and Milky stork with an overall predicted accuracy of 94.8 and 90.0%, respectively. However, TL measurements generated a lower predicted accuracy level of 86.2% and a same accuracy level of 90% on the sex classification of individuals from Painted and Milky stork, respectively. By comparing the measurements of both species, only the average BL measurements of the Milky storks were significantly lower than that of Painted storks (t-test, P80.001). The logistic regression equation in this study may serve as a simple and more practical option for sexing Milky and Painted storks for their breeding and conservation programmes.