Financial indicators (ratios) are calculated from the data found in basic financial statements. Balance sheets, income statements and cash flow statements are used in making different analyses for different information users. These indicators can be used to make inferences about a company's financial condition and its operations and attractiveness as an investment. They also can be used to analyze trends and compare companiesí financial performance and situation to other firms. This study empirically examines the common and distinctive financial indicators of steady and unsteady successful big manufacturing companies in Turkey by using data mining methodology. In this framework, the variables that affect the success of the company are identified by using logistic regression analysis. Then the differential values of the indicators are identified by using decision trees. Decision tree analysis is used for checking the logistic regression analysis results. As a result of different tries, the most appropriate decision tree algorithm, C&RT (Classification and Regression Trees) has been selected. According to logistic regression analysis, current ratio, quick ratio, debt ratio, short term debt/total debts, inventory turnover ratio, CFFO/total assets and CFFF/CFFI variables are found to be significant at the 95% confidence level. The results also reveal that quick ratio, debt ratio, short term debt/total debts and inventory turnover ratio variables are found to be distinctive financial indicators for successful companies by using decision trees.