Identification of natural frequencies is one of the key tools for analyzing the dynamic behavior of gas and steam turbine blades and plays a critical role in power generation and aerospace industries. In lightweight and sensitive blades, the use of contact sensors such as accelerometers introduces additional mass and damping into the system, leading to increased errors in estimating natural frequencies. In this study, the natural frequencies of a turbine blade are measured using a non‑contact microphone‑based acoustic sensing method. The blade is suspended under free–free boundary conditions and excited by an impulse hammer, while the resulting vibration response is captured as an acoustic signal by a microphone. The signals are processed using a data acquisition system and the FFT algorithm to extract the natural frequencies. The experimental results are compared with finite‑element simulations performed in ANSYS. The data show that the proposed method can identify the blade’s natural frequencies with a relative error of less than 2%, and the corresponding phase transitions in the frequency response function confirm the validity of the non‑contact measurement approach.