In many cases, turbulence is superimposed on an unsteady organized motion of a mean flow. Indeed, large ranges of scales are involved in these flows, and it is important to investigate their characteristics and interactions. Thus, the time-frequency decomposition provided by the wavelet analysis appears an efficient tool that complements the classical approach and the Fourier transform. In this study, the wavelet decomposition (WD) method has been applied to the forced turbulent jet flows. The obtained results of the WD are compared with those of the other most common techniques such as proper orthogonal decomposition and phase averaging. In addition, the spectrogram of the signals has been presented for a visual representation of the frequency contents. it is shown that the WD is a successful tool to decompose the forced turbulent jet flows into its components for various axial distances, Re numbers, and forcing frequencies.