The application of robotics has evolved significantly through every industry. Although robots provide a wide range of motion, their lightweight components limit the rigidity at the tool center point (TCP). Consequently, industrial robots with serially arranged axes and conventional gear mechanisms have problems with kinematic accuracy when performing machining operations. Compensatory techniques involving joint stiffness determination and model-based predictions aim to compensate for displacement due to stiffness during the path generation. Innovative precision gearboxes can be used to reduce this displacement. The higher rigidity and lower backlash of precision gears compared to standard gears enable increased accuracy when carrying out production processes with industrial robots. A study at Fraunhofer IWU confirmed this by examining the impact of precision gear on a six-axis robot's accuracy during a milling process. However, all gears certainly would not have the same effect on a given process’s accuracy, and replacing all gears would inevitably lead to higher costs. Therefore, it is important to identify the gear with the most dominant effect to achieve the required accuracy. This paper presents a concept to develop a gear selection tool which utilizes robot data, a multibody simulation model along with gear parameters and process requirements to simplify gear selection for industrial processes. This tool aims to enable the customer/end-user to answer the question “Which gear needs to be replaced/installed in my robot in order to achieve the required/improved movement accuracy for an existing or new process?”.