This study aims at verifying the experimental results of a newly developed portable linear rock cutting machine (PLCM) and its usability for proper selection, design and predicting performance of TBMs instead of full-scale rock cutting machine. PLCM minimizes some of the disadvantages of full-scale linear rock cutting machine (FLCM) such as requiring experienced manpower to run the tests, large blocks of rock samples, which are usually difficult to obtain and expensive, and time consuming procedures. Relieved and unrelieved cutting tests at different depths of cut are performed in this study on different rock samples with the PLCM by using a mini-scale constant cross-section (CCS) disc cutter having a diameter of 145 mm and a tip width of 4.7 mm and the FLCM by using a real-life CCS disc cutter having a diameter of 432 mm and a tip width of 12 mm. Line spacing is 20 mm for mini scale disc cutter and 60-80 mm for real-life disc cutter in cutting tests in relieved mode. The results from both of the experimental devices are correlated for using prediction of cutting performance parameters of FLCM, which is commonly preferred and well-proven testing device for predicting the performance of any type of mechanical miner excavating hard rock. Then, another set of rock sample is obtained from Uskudar-Umraniye-Cekmekoy (UUC) metro tunnel construction site using EPB TBMs, of which their field performance (penetration and/or cutting rate, specific energy) and operational parameters (TBM thrust, cutterhead torque, power and rotational speed) are recorded. Based on the PLCM tests performed on the samples obtained from the field, the performance of the TBM is estimated theoretically (deterministically) and compared with the realized field performance to verify the results of the PLCM tests. The results indicate that the experimental cutting performances of the PLCM and the FLCM are well correlated and the PLCM can be used for predicting performance, design and selection of TBMs excavating hard rocks. Additional studies are required for developing more reliable models for predicting excavation performance.