The USGS ShakeAlert Earthquake Early Warning (EEW) system issues a warning to residents on the West Coast of the US seconds before damaging waves arrive, if the expected ground level shaking exceeds a certain threshold. However, residents in tall buildings may experience much greater motion due to the dynamic response of the buildings, as observed during the recent 2019 Ridgecrest earthquake. Therefore, there is an ongoing effort to extend the EEW system to include the contribution of building response in order to provide a more accurate estimation of the expected shaking intensity, especially for tall buildings. Unfortunately, the supposedly ideal solution of analyzing detailed Finite Element (FE) models of buildings under predicted ground motion time histories is not theoretically or practically feasible at the moment. The authors have recently investigated existing simple methods to estimate Peak Floor Acceleration (PFA) based on estimated Peak Ground Acceleration (PGA), showing these simple formulas are not suitable for PFA estimation unless the modal properties of the building and accurate ground motion response spectra are available. Instead, this paper explores another approach by extending the PEER PBEE (Performance-Based Earthquake Engineering) to EEW, considering that every component involved in building response prediction is uncertain in the EEW scenario. While this idea is not new and has been proposed by other researchers, it has two shortcomings: 1) the simple beam model used for response prediction is prone to modeling uncertainty, which has not been quantified, and 2) the ground motions used for probabilistic demand models are not suitable for EEW applications. In this paper, we address these two issues by incorporating modeling errors into the parameters of the beam model and by using a new set of ground motions, respectively. We demonstrate how this approach could practically work by utilizing data from a 52-story building in downtown Los Angeles. The criteria and thresholds for comparing the estimated PFA are beyond the scope of this study, but using those employed by previous researchers shows that if PGA is accurately estimated, this approach can predict the appropriate level of human comfort in tall buildings.