SPECT is a nuclear medicine tomographic imaging technique which uses gamma rays to produce images from a radioactive source. The source is either administered or injected into the patient and an attached computer process the information as an image. In medical imaging procedure, patients radiation dose are manage through appropriate dose optimisation protocol by various imaging centers. The protocol is designed to establish a balance between the injected activity and the quality of images produced. The aim of the study is to determine and design a GUI of the relationship between patient’s radiation dose from the injected activities and the image quality based on the signal to noise ratio. The study procedure involved three processes, the injected activities, which is administered to patients based on age, weight and gender, the process imaging technique based on image reconstruction method and the image quality, based on signal to noise ratio. Minitab statistical application tool was used to design a comprehensive clinical support application software based on mathematical model of patient’s preclinical information and administered activity. This was done by using experimental analytical modeling technique to determine BSI, from measured body height and weight based on age and gender. The Minitab regression modeling technique was then used to model the relationship between administered activities (potential patient dose) based on age and weight and image quality based on signal to noise ratio (SNR). So that with known patient’s height and weight and the injected activity, pre-imaging input parameters are determined, enabling dose estimate parameters to be predicted before the beginning of the imaging procedure. These were done in order to predict the expected SNR that will be good enough to answer all the clinical questions from the administered activities. This enable dose optimisation protocol to be established using a comprehensive clinical decision support application software for clinical application in SPECT imaging.