The partial or complete bed defluidization is an undesired phenomenon in industrial application involving fluidized bed operations. In the process of particle coating, the defluidization can be prevented by increasing the gas velocity and/or decreasing the coating suspension flow rate, if the changes in the hydrodynamics of the fluidization are early detected. For industrial applications, the use of a technique that can quickly identify the defluidization region is very important, avoiding loss of efficiency or even the necessity of shutting down the process. The purpose of the present work is to identify the defluidization region in a fluidized bed coating process using the Gaussian mean frequency, which is an alternative methodology based on pressure fluctuation analysis. Experiments were carried out in a Plexiglas column with a 0.143 m in inner diameter and 0.71 m in height, at a temperature of 70 ยฐC. Microcrystalline cellulose (MCC) of 325 ฮผm in diameter and an apparent density of 980 kg/m 3 was used as fluidizing particles, which was coated by a suspension based on Eudragitยฎ. All raw data sets of pressure in the plenum were collected at a sampling rate of 400 Hz, considering 2048 data points. LabViewยฎ 7.1 software was used for all data acquisition and signal processing. The results showed that the defluidization region can be clearly identified using the methodology employed. It also could have a high potential in industrial applications, especially for on-line control in order to avoid the defluidization region and consequently the efficiency loss of a coating process.