The study of self-sensing cementitious materials is a constantly expanding topic of study in the materials and civil engineering fields and refers to the creation and utilization of cement-based materials (including cement paste, cement mortar, and concrete) that are capable of sensing (i.e. measuring) stress and strain states without the use of embedded or attached sensors. With the inclusion of electrically conductive fillers, cementitious materials can become truly self-sensing. Previous researchers have provided only qualitative studies of self-sensing material stress-electrical response. The overall goal of this research was to modify and apply previously developed predictive models on cylinder compression test data in order to provide a means to quantify stress-strain behavior from electrical response. The Vipulanandan and Mohammed (2015) stress-resistivity model was selected and modified to predict the stress state, up to yield, of cement cylinders enhanced with nanoscale iron(III) oxide (nanoFe2O3) particles based on three mix design parameters: nanoFe2O3 content, water-cement ratio, and curing time. With the addition of a nonlinear model, parameter values were obtained and compiled for each combination of nanoFe2O3 content and water-cement ratio for the 28-day cured cylinders. This research provides a procedure and lays the framework for future expansion of the predictive model.