We present a new approach to evaluation of bankruptcy risk of firms based on the rough set theory. The concept of a rough set appeared to be an effective tool for the analysis of information systems representing knowledge gained by experience. The financial information system describes a set of objects (firms) by a set of multi-valued attributes (financial ratios and qualitative variables), called condition attributes. The firms are classified into groups of risk subject to an expert's opinion, called decision attribute. A natural problem of knowledge analysis consists then in discovering relationships, in terms of decision rules, between description of firms by condition attributes and particular decisions. The rough set approach enables one to discover minimal subsets of condition attributes ensuring an acceptable quality of classification of the firms analysed and to derive decision rules from the financial information system which can be used to support decisions about financing new firms. Using the rough set approach one analyses only facts hidden in data, it does not need any additional information about data and does not correct inconsistencies manifested in data; instead, rules produced are categorized into certain and possible. A real problem of the evaluation of bankruptcy risk by a Greek industrial development bank is studied using the rough set approach.