One of the key tasks in performing forensic medical examinations on unidentified individuals is determining biological age. Such tasks are being successfully accomplished due to advances in science and technology, particularly through the use of modern medical imaging techniques. In this study, we propose an age prediction model based on chest computed tomography (CT) imaging. The study sample comprised 175 chest CT images from male and female individuals with an age range of 18 to 79 years. The areas assessed included the degree of fusion of the manubriosternal, xiphosternal, and costosternal joints. Differentiation of the fusion stages was performed using a unique scoring scale we developed, supported by reference images illustrating the stages of ossification in sternal synostoses. Based on the results of the regression analysis, a mathematical model for age prediction was developed, yielding a mean absolute error of 7.28 years for both sexes.