This study introduces a method for evaluating the design capacity of a structural system at different limit states using nonlinear analysis (NLA). At the core of this approach lies the Global Factor Method (GFM), which simplifies complex structural behaviour into concurrent local failure mechanisms (LFMs). These LFMs are organized hierarchically, based on their series or parallel arrangement within the system, allowing for the derivation of a global factor used for estimating the design value of the global capacity, matching a given target probability. Notably, this method eliminates the need for alternative metrics like interstorey drift or post-peak capacity reduction, directly identifying global failure as driven by concurrent LFMs. Its practical application involves conducting two nonlinear analyses—one with mean values of the basic variables and another accounting for uncertainties in the LFMs. Correlation among LFMs is handled pragmatically, by considering extremes of zero and full correlation to enhance usability in practical design and assessment scenarios. The efficiency of the proposed method is demonstrated through its application to a reinforced concrete frame modelled using OpenSeesPy. The developed method is intended for practical use in NLA, specifically tailored for practitioners seeking an accessible approach to estimate design values within a simplified framework. In a sense, it provides an important step toward formalizing design capacity assessment within everyday engineering practice. While it is not a fully rigorous solution, it offers a reasonably accurate estimate of the design capacity, bridging the gap left by current codes, which have so far overlooked this critical aspect in NLA.