A free-space dielectric arrangement with X-band coaxial-to-waveguide adapters was used to non-destructively assess shell egg quality. Scattering parameters in the microwave spectral range (8–12 GHz) were measured in reflectance and transmittance modes from eggs placed in three orientations. Partial least squares regression was applied to predict egg quality indices, including air cell height (ACH), yolk coefficient (YC), thick albumen height (TAH), Haugh unit (HU), and albumen pH. Prioritizing PR_S22 spectrum in horizontal 1 orientation, several feature selection methods were employed to identify the most effective frequencies. Artificial neural networks (ANNs) were then used to develop predictive models based on influential frequencies. The competitive adaptive reweighted sampling method consistently outperformed others, yielding robust ANN models with excellent residual predictive deviation values of 4.80, 4.00, 3.27, 3.03, and 3.72 for ACH, YC, TAH, HU, and albumen pH, respectively. This study demonstrates the effectiveness of free-space dielectric arrangements in predicting egg quality.