Business process mining is a powerful tool to retrieve the valuable business knowledge embedded in existing information systems. The effectiveness of this kind of proposal is usually evaluated using recall and precision, which respectively measure the completeness and exactness of the retrieved business processes. Since the effectiveness assessment of business process mining is a difficult and error-prone activity, the main hypothesis of this work studies the possibility of obtaining thresholds to determine when recall and precision values are appropriate. The business process mining technique under study is MARBLE, a model-driven framework to retrieve business processes from existing information systems. The Bender method was applied to obtain the thresholds of the recall and precision measures. The experimental data used as input were obtained from a set of 44 business processes retrieved with MARBLE through a family of case studies carried out over the last two years. The study provides thresholds for recall and precision measures, which facilitates the interpretation of their values by means of five linguistic labels that range from low to very high. As a result, recall must be high (with at least a medium precision above 0.56), and precision must also be high (with at least a low recall of 0.70) to ensure that business processes were recovered (by using MARBLE) with an effectiveness value above 0.65. The thresholds allowed us to ascertain with more confidence whether MARBLE can effectively mine business processes from existing information systems. In addition, the provided results can be used as reference values to compare MARBLE with other similar business process mining techniques.