In a world impacted by economic instabilities like the coronavirus disease 2019 (COVID-19) pandemic, accurately predicting corporate bankruptcies is increasingly vital. This study focuses on refining bankruptcy prediction models using multiple discriminant analysis for manufacturing firms in the Visegrad Four countries—Slovakia, Poland, Hungary, and the Czech Republic. Utilizing a comprehensive dataset from the Orbis database, which encompasses 28 variables from 12,027 companies, the authors aim to predict bankruptcy up to 3 years in advance. Our analysis reveals significant variations in financial indicators across different prediction timelines. The 1-year prediction model highlights the importance of Working Capital to Total Assets and Return on Assets for assessing short-term financial health, with the relevance of X04 diminishing overtime. In contrast, net income to total assets and short-term liabilities to total assets evolve from short-term liquidity indicators to long-term profitability and liability markers, respectively. Longer term models show that variables like operating profit to total assets and total liabilities to total assets become increasingly significant, suggesting growing financial pressures. Factors such as the age of the companies, their sizes, and other regions including Hungary and Poland did not significantly impact the results. The consistent inclusion of the Czech Republic dummy variable highlights unique regional influences that are crucial for understanding bankruptcy risk. These models offer valuable insights for firms to enhance their financial resilience and provide actionable data that could influence regulatory policies and corporate strategies to mitigate bankruptcy risks in the future.