Background: The lung capacity prediction formula in Korea is an important judgment standard. Since there is no appropriate lung capacity prediction formula, various prediction formulas are used for foreigners such as Northeast Asians. The purpose of this study is to develop a lung capacity prediction equation by selecting data and setting the selection criteria for normal subjects in accordance with international standards through strict quality control, and to propose a new prediction model. Design: Preliminary feasibility study Methods: A total of 857 people who met the criteria for normal people were finally collected. The tester used for the lung capacity test was the V-Max Encore 22 (Carefusion, California, USA), which is a lung capacity tester proposed by the Korean Society of Tuberculosis and Respiratory Medicine and satisfies accuracy and precision. Among the indicators measured using spirometry, forced vital capacity (FVC), forced expiratory volume in 1 second (FEV1), forced expiratory volume ratio in 1 second (FEV1/FVC), forced mid-expiratory flow (Forced expiratory flow 25-75%, FEF25-75%) and peak expiratory flow (PEF) values were collected. Results: This study confirmed a significant correlation between age, height, weight, and pulmonary function indicators. Additionally, it found a correlation between body mass index, which considers the diversity of physical conditions, and pulmonary function indicators. Graphs depicting age-specific pulmonary function indicators by gender, presented as generalized additive model results from collected data, showed a pattern where both FVC and FEV1 increased until the mid-20s and then gradually decreased with aging. FEV1% and PEF exhibited a continuous decrease with aging. Conclusion: This study confirms that there is a significant correlation between weight and pulmonary function in the prediction formula for lung capacity. Additionally, it verifies the correlation between body mass index, which considers the diversity of physical conditions, and pulmonary function. The study suggests that the predicted values are relatively low due to factors such as aging and environmental influences like COVID-19. This preliminary study holds clinical significance for improving the diagnostic accuracy of respiratory symptoms in the elderly.