Computed tomography (CT) radiation dose reduction is vital without compromising image quality. The aim was to determine the effects of patient characteristics on the received radiation dose and image quality in chest CT examinations and to be able to predict dose and image quality prior to scanning. Consecutive 230 patients underwent routine chest CT examinations were included. CT examination and patients input parameters were recorded for each patient. The effect of patients' demographics/anthropometrics on received dose and image quality was investigated by linear regression analysis. All parameters were evaluated using an artificial neural network (ANN). Of all parameters, patient demographics/anthropometrics were found to be 98% effective in calculating dose reduction. Using ANN on 60 new patients was more than 90% accurate for output parameters and 91% for image quality. Patient characteristics have a significant impact on radiation dose and image quality. Dose and image quality can be determined before CT. This will allow setting the most appropriate scanning parameters before the CT scan.