Abstract: A system and method for screening and monitoring progression of subjects' health conditions and wellbeing, by the analysis of their voice signal. According to one embodiment, a system is provided that records voice samples of subjects and evaluates, in real time, the severity of their health condition based on vitality biomarkers. The vitality biomarkers are the construct of machine learning and deep learning models trained in an offline procedure. The offline training procedure is optimized to associate between (a) acoustic features and/or image representations of training cohort subjects' pre-recorded voices; and (b) their vitality score, extracted from their medical records. In the training procedure, the vitality scores of the training cohort subjects is heuristically defined as a function of the speaker age at the time of recording and the duration elapsed between the time of recording and available clinical events, with emphasis on the time of death when available.