The Volterra series-based frequency-domain methodology, along with the associated frequency response functions (FRFs)of nonlinear systems, fundamentally depends on the accurate computation of the Generalized Frequency Response Functions (GFRFs) and the corresponding output spectra. While analytical derivation of these FRFs is feasible through recursive algorithms, as previously discussed, they can also be obtained via numerical techniques—provided that the system model is known or sufficient experimental data are available. A critical challenge in the numerical implementation (refer to Section 3 of Chapter 2) lies in the accurate estimation of each order of the output spectrum, particularly in the presence of truncation errors.This raises the essential question of whether it is possible to reliably compute low-order output spectra (typically up to second or third order in practical applications) with limited truncation while maintaining high fidelity. To address this issue, a truncation error theory is developed and introduced in this chapter. This theoretical framework establishes the foundational principles for efficiently and accurately computing each order of the output spectrum using a minimal truncation order. Unlike conventional curve-fitting approaches, this theory enables a principled and systematic treatment of truncation effects, thereby opening new avenues for advanced applications of Volterra series-based frequency-domain analysis in nonlinear system modeling and design.