Forecasting external public debt under conditions of uncertainty is important as it allows the country to respond adequately to economic and financial challenges, promotes efficient management of financial resources, formation of a stable financial policy and ensures the country's external debt security, which are critical elements for ensuring economic sustainability and sustainable development. The article's main purpose is to critically analyze and apply existing time-series forecasting methodologies to determine the future values of Ukraine's external public debt in conditions of uncertainty caused by the still unresolved consequences of the COVID-19 pandemic and russia's invasion and full-scale war in Ukraine. Using three forecasting methods, namely trendline extrapolation, exponential smoothing, and autoregressive and moving average models, the paper forecasts the volume of external public debt until 2029 and presents a graphical representation of the debt dynamics from 2011 to 2029. The most pessimistic forecast for the growth of external public debt was revealed when applying the method of data extrapolation based on the trendline. A comparative analysis of the forecast values for the three forecasting methods has revealed common trends in the growth of public debt, as well as the key advantages and disadvantages inherent in each model. Importantly, the article emphasizes the common risks identified in forecasting Ukraine's external debt using time series analysis models, including the problem of achieving only short-term forecasting accuracy and insufficient flexibility taking into account complex and unexpected changes that may arise in conditions of uncertainty and economic instability. The results of the study provide valuable information for policymakers and stakeholders trying to navigate the complexities of managing external public debt under uncertainty.
