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The increasing fleet of aging aircrafts has resulted in an increasing demand for cost effective nondestructive evaluation (NDE) techniques that are accurate, reliable, and easy to use. Magneto-Optic Imaging (MOI) is such a technique, which has gained wide acceptance for detection of both surface and subsurface defects in multi-layer aircraft structures. The main advantage of MOI is rapid inspection and ease of interpreting image data in contrast to complex impedance signals from conventional eddy current instruments. One missing piece of the puzzle for advanced MOI systems is how to quantitatively analyse the MO images, and understand the detectability limits when image data are acquired under varying operational conditions. This paper presents a probability of detection (POD) study that is conducted using both simulation model-predicted and experimental MO image data. Simulated panels from a 3-D FEM model and experimental panels with machined defects are used to generate data for interpretation by human inspectors or automated systems, and subsequently for POD studies. The POD curves demonstrate the merits in optimizing inspection parameters that maximized the performance of current MOI systems. Parameters quantifying the detectability of MO image data using skewness functions are also presented and discussed.