Abstarct: Classification of rock mass, the main bone structure of empirical design surface, indicates the quality of engineering rock mass. The classification systems work by extracting data from the characteristics and structure of the study area's rock mass using graphs and tables provided in each classification method, and inputting the data into data management and analysis software such as Excel for calculation. This method is time-consuming and prone to human error. Today's technology has provided tools to humans to work faster and more accurately. One of these technologies is smartphones with powerful processors, advanced cameras, large display capabilities, various sensors including GPS, accelerometers, compasses, and the simplicity of developing applications on smartphones provide a great opportunity for researchers to use this hardware and software platform. In this research, using the smartphone application platform to create an engineering tool for calculating rock mass classifications by methods such as RMR, Q, GSI, RMI, Qslope, SMR, as well as selecting tunnel maintenance methods by RMR, Q, RMi, and rock wedge methods by SMR has been addressed. The RMC application is developed in the Android Studio environment and written in the Java programming language. In various methods, an effort has been made to replace quantitative methods as much as possible with tables. In the RMR method, to calculate UCS, RQD, and spacing, relationships have been substituted for scoring through tables using the presented graph fits. For the GSI method, a quantitative method presented by Hoek and colleagues has been used. Two methods have been designed for classification in the application; in the first method, the user can calculate each classification separately and receive the results; in the second method, the data is entered once, and the necessary classifications are provided to the user. The program's operation involves receiving initial data while extracting by the user, performing the classification, and selecting maintenance by the program. After classification is performed, the final report presents the classification results and input data in PDF or Excel output. To validate the RMC program, several samples from past studies were selected for each method, and the values of the samples were calculated and compared in Excel and RMC software. The results demonstrate the efficiency and accuracy of RMC calculations. Due to the higher calculation accuracy of RMC in terms of decimal calculation compared to Excel, there is minimal difference in some samples between the values calculated in Excel and RMC.