Magnetic Levitation Systems (MLS) are usually highly non-linear systems with a great sensitivity to the size of the control input. Therefore, special emphasis should be placed on the correct identification of all unknown MLS parameters. This paper describes the principle and procedure for identifying laboratory plant CE 152 MLS with an emphasis on automatically processing identification data. Moving-Average Filter (MAF) and Fast Fourier Transform Filter (FFTF) methods are compared to filtering input data noise. Key parameters are then estimated using the Least Squares Method (LSM). The results are verified in simulation and real-world experiment using a simple PID controller.