Abstract Objective To improve diagnosis of early Alzheimer's disease (AD), i.e., prodromal AD, by an automated quantitative tool combining brain perfusion single-photon emission computed tomography (SPECT) images and memory tests scores in order to be applied in clinical practice. Patients and methods In this prospective, longitudinal, multi-centric study, a baseline 99mTc-ECD perfusion SPECT was performed in 83 patients with memory complaint and mild cognitive impairment (MCI). After a 3-year follow-up, 11 patients progressed to Alzheimer's disease (MCI-AD group), and 72 patients remained stable (MCI-S group), including 1 patient who developed mild vascular cognitive impairment. After comparison between the MCI-S and MCI-AD groups with a voxel-based approach, region masks were extracted from the statistically significant clusters and used alone or in combination with Free and Cued Selective Reminding Test (FCSRT) scores for the subject's categorization using linear discriminant analysis. Results were validated using the leave-one-out cross-validation method. Results Right parietal and hippocampal perfusion was significantly ( p < 0.05, corrected) decreased in the MCI-AD group as compared to the MCI-S group. The patients’ classification in the MCI group using the mean activity in right and left parietal cortex and hippocampus yielded a sensitivity, specificity, and accuracy of 82%, 90%, and 89%, respectively. Combination of SPECT results and FCSRT free recall scores increased specificity to 93%. Conclusion The combination of an automated quantitative tool for brain perfusion SPECT images and memory test scores was able to distinguish, in a group of amnestic MCI, patients at an early stage of AD from patients with stable MCI.