The article is concerned with determining the main predictors of bankruptcy in construction organizations in the Russian Federation. Probabilistic prediction of bankruptcy is relevant for both individual companies and sectors of the national economy. Developed a long time ago, the existing bankruptcy prediction methods do not consider the industry specifics of organizations. The article investigates the mechanism for probabilistic prediction of bankruptcy based on logit models. Criteria affecting the bankruptcy probability were substantiated; a mathematical model was proposed to calculate the probability. The provided model was tested in a real company. Based on the sample of small and medium-sized construction companies, the author proposed a logit model reflecting the main factors affecting the financial state of construction companies in Russia and, therefore, the likelihood of their bankruptcy. Testing the model on the actual data from the construction enterprises showed its high predictive power. The study results allow predicting the bankruptcy in construction organizations by means of logit models.

The paper examines some foreign and domestic methods of forecasting bankruptcy of enterprises in order to apply them in the largest construction organizations in Russia. The empirical basis of the study is the construction companies that are comparable in size, revenue, and market share. Their annual financial statements preceding the analysis are the information base of calculations. The quality of forecasts has been checked on independent indicators’ calculations of financial analysis, as well as using data from financial markets and share prices under studied companies. The result of the research is the selection of models that gives the most correct forecast of the financial situation of a company in the construction industry. It has been also revealed that models for predicting financial insolvency of enterprises has not been able to assess changes in financial stability in the short term. Therefore, the author compares calculation results with data of financial markets. As a result, it was found that models which demonstrate the greatest predictive ability correlate with the results of independent financial analysis, as well as with data of financial markets regarding the share price dynamics of construction companies. The paper provides recommendations on approaches to choosing models for analyzing the probability of bankruptcy and can be useful for specialists of financial and analytical services to predict the financial insolvency of construction business.