Structural health monitoring (SHM) detects, localizes, and quantifies seismic damage, but does not provide tools to assess further damage and potential collapse in subsequent shocks. Models built from SHM results would enable these further analyses, and enhance decision-making. This paper presents an automated model creation method, converting proven hysteresis loop analysis (HLA) SHM results into nonlinear foundation models for immediate use. Accuracy, complexity, and automation are assessed using experimental data from a 3-storey full-scale structure tested at the EDefence facility in Japan over 6 events. For all cases, the simplified nonlinear modelling method achieved a mean (5-95% Range) peak displacement error of 0.82 (0.17, 4.09)mm, and average cross correlation coefficient Rcoeff=0.82. The simplified modelling method captures essential dynamics very well given nonlinear HLA-identified stiffness changes as inputs, is readily automated, and is thus suitable for initial analysis on damage mitigation. This method extends proven SHM methods from a damage identification tool into readily automated application of its results for further decision-making, creating far greater utility for engineers.