Predictive Diagnostics of Viability

Predictive diagnostics is becoming an increasingly important scientific methodology for identifying early signs of change in complex systems before critical failures become observable. Existing approaches to predictive diagnostics have achieved significant success in engineering, healthcare, environmental monitoring, economics, and artificial intelligence. Nevertheless, contemporary predictive methods are generally focused on forecasting specific failures or operational events rather than evaluating the long-term viability of systems as multidimensional organizational entities. This article proposes the conceptual foundations of Predictive Diagnostics of Viability within the framework of Vitology. Rather than predicting isolated failures, the proposed methodology focuses on identifying early organizational changes that influence the long-term preservation, restoration, and enhancement of system viability within the Space of Harmony. Within this framework, predictive diagnostics integrates conceptual models of viability, quantitative indicators, mathematical representations, computational algorithms, viable digital twins, empirical observations, and artificial intelligence into a unified computational methodology. Such integration enables continuous evaluation of organizational trajectories, early recognition of declining viability, comparative analysis of alternative developmental scenarios, and scientifically grounded support for Harmony Navigation. Artificial intelligence functions as a methodological partner that continuously refines predictive models, identifies multidimensional organizational regularities, estimates future developmental tendencies, and assists scientific investigation while remaining subordinate to conceptual theory, mathematical rigor, and empirical validation. The proposed methodology establishes scientific foundations for future predictive systems applicable to natural, biological, ecological, social, organizational, technological, and artificial systems. By integrating predictive diagnostics with the principles of Vitology, the proposed framework contributes to the emergence of a unified interdisciplinary methodology for forecasting, preserving, restoring, and increasing the viability of complex systems. Keywords Vitology, predictive diagnostics, viability, predictive modeling, Space of Harmony, Harmony Navigation, artificial intelligence, viable digital twins, computational modeling, systems science, early warning systems, multidimensional analysis, computational simulation, empirical validation, interdisciplinary