For the aim of efficient direct current (DC) motor control, accurate model estimation is required to be derived. However, the DC motor model is estimated and derived via the system identification procedure and the objective of current paper is to illustrate two different methodologies for the mentioned procedure. First methodology is the linear one in which the DC motor is proposed to work in a linear (stable) range and it gives better data fit than the second methodology through which we implement a PRBS (Pseudo Random Binary Sequence) test on the DC motor. Indeed, even though the PRBS methodology gives less data fit, it is more suitable for matching the real time working conditions under control algorithms implementation on the DC motor due to the load disturbance rejection and other working requirements.