Abstract: This article is a study of the possibility of improving scientific and methodological approaches to determining the bankruptcy of insolvent organizations. The paper discusses modern methods of bankruptcy forecasting, as well as the author's methodology for identifying "pre-bankruptcy" for tax administration purposes. The purpose of the presented research is to improve scientific and methodological approaches to determining the situation preceding the onset of insolvency (bankruptcy) of legal entities for the purposes of tax administration. The novelty of the present study lies in the development of an algorithm for determining control ratios that make it possible to identify the possible insolvency of legal entities for tax administration purposes. The object of the study is the economic relations formed during the bankruptcy procedure of insolvent organizations.The basis of the research methodology is formed on the basis of general scientific and special research methods, including methods of comparative analysis, a method of summarizing results when formulating conclusions and presenting priority areas, a method of system analysis and expert assessment. The research results are primarily aimed at improving the efficiency of tax administration of insolvent organizations through a set of preventive measures by tax authorities aimed at financial recovery of organizations, identifying problematic taxpayers at risk of insolvency (bankruptcy), as well as providing an opportunity to voluntarily restructure the assets and liabilities of organizations. At the same time, the prospects for further research lie in adapting foreign neural networks to predict corporate bankruptcies and create domestic ones.

Keywords: methodology, bankruptcy estate, neural network, creditors, forecasting, tax administration, debtor, pre-bankruptcy period, insolvency, bankruptcy institute