Several popular frequency-based fatigue damage models (Wirsching and Light, Ortiz and Chen, Larsen and Lutes, Benascuitti and Tovo, Benascuitti and Tovo with α.75, Dirlik, Zhao and Baker, and Lalanne) are reviewed and assessed. Seventy power spectrum densities with varied amplitude, shape, and irregularity factors from Dirlik’s dissertation are used to study the accuracies of these methods. Recommendations on how to set up the inverse fast Fourier transform to synthesize load data and obtain accurate rainflow cycle counts are given. Since Dirlik’s method is the most commonly used one in industry, a comprehensive investigation of parameter setups for Dirlik’s method is presented. The mean error and standard deviation of the error between the frequency-based model and the rainflow cycle counting method was computed for fatigue slope exponent m ranging from 3 to 12. The results showed Ortiz and Chen, Benascuitti and Tovo with α .75, Larsen and Lutes, Dirlik, and Benascuitti and Tovo to be significantly more accurate than Lalanne and Zhao and Baker. These five models have a tendency for the error variation to increase as the fatigue exponent m increases. For this study using Dirlik’s seventy spectra, Ortiz and Chen, Benascuitti and Tovo with α .75, and Larsen and Lutes Single Moment methods had lower mean error than Dirlik’s method.