Combustors of modern gas turbines for power generation and mechanical drive are predominantly operated in premixed mode, which is sensitive to coupling between flame dynamics and combustor acoustics. In practice, combustor flames tend to drive instabilities at certain eigenfrequencies of the systems, according to the classical Rayleigh criterion. In order to guarantee combustor stability in the entire operation range of the engine it has to be avoided under all circumstances that the flame excites the system beyond its damping potential. One option to accomplish this is to provide sufficient damping capabilities of the combustor system so that the decay of acoustic energy inside the system always exceeds the excitation provided by the flame. Experimental methods for the determination of combustor damping rates therefore may become a valuable tool for combustor design in the future. In the past, methods with different accuracy, complexity and capabilities have been developed to gain experimental access to decay rates of the acoustic energy inside combustor systems. In this study we compare accuracy and capabilities of three different time-domain methods that allow the determination of pressure decay rates from experimental dynamic pressure traces: A simple exponential fit to the measured dynamic pressure, a method based on the decay of acoustic energy and a newly developed statistical method are examined. In the first step, the methods are tested using artificially generated test signals. The simple signals decaying exponentially with the known rate a are of pure sinusoidal shape and have discrete frequencies. As practical dynamic pressure traces are in general corrupted with noise, in the second step of the analysis a certain amount of random noise is added to the test signal. The last step of the analysis involves realistic pressure signals obtained from a simple duct with throughflow. The results obtained from the different methods are compared with each other and differences regarding performance, accuracy, robustness as well as computational costs are presented.