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Nowadays, due to the worldwide crisis, there is a necessity to predict and make a prognosis for the future development of the companies from the view of their financial health. Mainly mining organizations in Slovakia face a problem with creditworthiness when a number of companies declared bankruptcy. The paper has the ambition to predict development in chosen Slovakian mining organization through the most used bankruptcy and bonity models, which brings results, serving for comparing with companies in time and sector. The results were evaluated according to the individual areas of financial position that influenced the development the most. Such results are profitable for the sustainable development of mining organizations together with providing the energetic independence of the countries. [ABSTRACT FROM AUTHOR]

The actual scientific research of development of information models of representation of fuzzy knowledge at an estimation of creditworthiness of the enterprises of the coal industry of Ukraine and perfection of a fuzzy mathematical model of an estimation of creditworthiness of the enterprises is carried out. Based on settheoretic analysis, a set of 11 criteria for assessing the creditworthiness of enterprises is formed and divided into 3 groups: indicators of financial stability, analysis of profits and losses, the efficiency of enterprise management. A membership function is constructed for each criterion, which will reveal the uncertainty in the input data, leading to a normalized form for comparison. To construct membership functions, a study was conducted to determine their type and type, as well as the parameters of membership functions based on the experience of credit experts and data sets on indicators, using real financial reports of Ukrainian coal industry enterprises for 2020. The improved fuzzy mathematical model for assessing the creditworthiness of enterprises, which reveals the vagueness of input data, derives the assessment of creditworthiness based on the reasoning of the decision-maker (DM), determines the linguistic level of ability to repay financial obligations on time. Based on the built model, a general six-step algorithm is constructed, which can be quickly implemented in the software product. The developed information model and the improved fuzzy mathematical model were tested on real data of credit assessment of the Lvivugol State Enterprise of Ukraine. Outcome, models, and approaches to presenting fuzzy knowledge for indicators of creditworthiness assessment of Ukrainian coal industry enterprises, which will be a model for other countries to follow. [ABSTRACT FROM AUTHOR]