We present a new method of extracting information on average vapor distribution in a cavitating flow based on statistical processing of PIV data for a liquid phase. For this, vectors on instantaneous velocity fields are analyzed over the entire statistical ensemble of instantaneous realizations considering their status: valid—vectors that passed validation procedures, outliers—the ones with incorrect values, out-of-flow—those calculated on insufficient number of seeding particles (tracers), masked—they correspond to unilluminated flow regions. The suggested approach is based on the two basic principles: absence of the tracers in the vapor phase and statistical independence of the successive measurements. The case study is performed for a cavitating 2D symmetric hydrofoil under unsteady cloud cavitation conditions with regular shedding of large-scale cloud cavities. Comparing statistical distribution laws in different flow regions makes it possible to recognize the stable sheet cavity and its pulsating part and determine the location of cloud cavity detachments. This approach for PIV data analysis is shown to be an effective tool to characterize time-averaged distribution of the dispersed phase in cavitating flow based merely on velocity measurements for the liquid phase. Using it allows one to substantially reduce consumption of computational resources and save time when investigating the structure of cavitating flows, limiting to standard PIV measurements in liquid. This method can be also applied to analyze the structure of other types of dispersed two-phase flows.