One of the critical steps in the development of an analytical technique is to confirm that its experimental response correlates with predictions derived from the theoretical framework on which it is based. This validates the technique quantitatively and, in the case of a biosensor, facilitates a correlation of the sensor's output signal to the concentration of the analyte being tested. Herein we report studies demonstrating that the quantitative response of arrayed imaging reflectometry (AIR), a highly sensitive label-free biosensing method, is a predictable function of the probe and analyte properties. We first incorporated a standard one-site Langmuir binding model describing probe-analyte interactions at the surface into the theoretical model for thickness-dependent reflectance in AIR. This established a hypothetical correlation between the analyte concentration and the AIR response. Spectroscopic ellipsometry, surface plasmon resonance, and AIR were then used to validate this model for two biomedically important proteins, fibroblast growth factor-2 and vascular endothelial growth factor. While our studies demonstrated that the 1:1 one-site Langmuir model accurately described the observed response of macrospot AIR arrays, either a two-site Langmuir model or a Sips isotherm better described the behavior of AIR microarrays. These studies confirmed the quantitative performance of AIR across a range of probe-analyte affinities. Furthermore, the methodology developed here can be extended to other label-free biosensing platforms, thus facilitating a more accurate and quantitative interpretation of the sensor response.