Objective To investigate the correlations among critical parameters of the internal nasal valve (INV) including unilateral cross-sectional area of the INV(A_INV-R,A_INV-L), total cross-sectional area of the INV(A_INV), unilateral height of the INV (H_INV-R, H_INV-L), unilateral angle of the INV(α_INV-R、α_INV-L) and the sum of INV angles(α_INV).Methods Maxillofacial computed tomographic images from 40 Han adults (20 males, 20 females; age ranged from 20 to 80 years old and 50% with age < 50 years old) without nasal diseases were applied to reconstruct the three-dimensional nasal airway models. After identifying the INV plane, the following parameters were measured: A_INV-R, A_INV-L, A_INV, H_INV-R, H_INV-L, α_INV-R and α_INV-L. Based on the morphological characteristics of INV, the prediction model was proposed as unilateral A_INV=W_INV×H_INV/2=tan[radians(α_INV)]×(H_INV)²/2, and the calculated A_INV based on the model was compared with the measured A_INV. Correlation analyses among the INV parameters, ages and genders were performed.Results There were no statistic differences but good correlations between the calculated and the measured values: A_INV-L(Z=-1.075，P＞0.05；r=0.766 2，P＜0.01), A_INV-R(t=-1.238，P＞0.05；r =0.818 2，P＜0.01)and A_INV(Z=-1.156，P＞0.05；r=0.799 3，P＜0.01). Comparison of the INV parameters between different sides showed that A_INV-R was larger than A_INV-L, which could be explained by the larger α_INV-R(t=-3.081,-2.029，P<0.05). Comparison of the INV parameters between different genders revealed that A_INV-L, A_INV-R and A_INV of the male group were larger than those of the female group, which could be explained by the larger H_INV-L and H_INV-R of the male group (t=-2.405, -3.336, -3.297, -4.223,-4.041，P<0.05). Comparison of the INV parameters between different age groups disclosed that A_INV-L and A INV of the young group (＜50 years old)were larger than those of the old group (≥50 years old), which could be explained by the negative correlation between A_INV-L, A_INV and age (r_s=-0.519 8,-0.433 1, P<0.01). Further, the comparison of the left and right INV parameters from the same age group showed significant differences between α_INV-R and α_INV-L, A_INV-R and A_INV-L in the old group(Z=-2.726, -2.987, P<0.01), this negative correlation might be related to the decrease of α_INV-L in the process of aging. Correlation analyses demonstrated that α_{INV R-L} was positively correlated with age (r=0.3428，P<0.05), A_{INV R-L} was positively correlated with α_{INV R-L} (r=0.710 9，P<0.01), and the measured A INV R-L was positively correlated with the calculated (r=0.779 5，P<0.01).Conclusion In this study, the proposed prediction model of unilateral A_INV can not only assess parameters of INV with good correlations between the calculated and the measured values, but also interpret the differences between sides, genders and age groups, as well as the negative correlations among α_INV-L, A_INV-L, A_INV and age.