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The problem of determining the search ranges for the optimal values for the main parameters in the random forest (RF) algorithm in order to reduce the time spent on developing RF classifier has been considered. The aim of the work is to obtain formulas for determining the search range for the values of RF classifier parameters. Formulas are obtained based on the results of experimental research on the development of RF classifiers using various sets from machine learning data repositories. The results of experimental research on the development of RF classifiers using training and test sets formed on the basis of the analyzed datasets have been presented. Formulas for graphical dependencies for assessing the quality of classification on the test set and development time have been obtained in general form. The recommendations on the application of the proposed formulas in the development of RF classifiers have been given.