Introduction: Height and weight measurements are required for the assessment of nutritional status. However, it is difficult to measure these parameters in nonambulatory persons. Hence, simple predictive equations that estimate these measurements using various anthropometric measurements are necessary. Methods: A total of 441 Asian-Chinese adults (174 males, median age = 32.5, IQR: 27.8 years; 267 females, median age = 34.6, IQR: 28.5 years) were used to build height and weight sex-specific prediction equations. An additional 111 Asian- Chinese adults (44 males, median age = 31.1, IQR: 25.0 years; 67 females, median age = 30.6, IQR: 25.6 years) were used to validate the newly developed prediction equations. Results: The best predictive model for height included arm length, knee height measurements and age (R2 = 0.70, standard error of estimate [SEE] = 3.38 for males; R2 = 0.71, SEE = 3.14 for females). The best weight predictive model included age, arm circumference and waist circumference (R2 = 0.79, SEE = 4.66 for males; R2 = 0.78, SEE = 4.38 for females). The new predictive models for height and weight have non-significant prediction biases as compared to the Cereda et al. (2010) and Ross equations, respectively. Conclusion: Height and weight predictive equations with a higher degree of accuracy have been developed for Asian Chinese adults.