Proteins can interact with one another by an interface composed of two proteins. Some of the interface residues – called hot spots – have the greatest impact on binding energy in a protein complex. This paper introduces the application of continuous wavelet transform based on the fast Fourier transform (CWTFT) to the analysis of hot spots in proteins. The basis of the algorithm is extraction of features from spectra obtained by using CWTFT with different wavelet functions including Morlet, \(m^\text {th}\) order derivative of Gaussian, Paul and Bump wavelets. Then, the classifiers that are able to separate hot spot from non-hot spot residues according to these features are applied. The algorithm was evaluated by using data sets containing 30 proteins. From the number of tested classifiers the best 10 models were preferred. The classifiers achieved sensitivity of 52%–71%, specificity of 70%–83% and accuracy of 70%–74%. The analyses show that the method combining CWTFT and classification algorithms is able to identify hot spot residues with valuable results.