In this paper, the effects of an electron beam on X-pinch-produced spectra of L-shell Mo plasma are investigated for the first time by principal component analysis (PCA); this analysis is compared with that of line ratio diagnostics. A spectral database for PCA extraction is arranged using a non-Local Thermodynamic Equilibrium (non-LTE) collisional radiative L-shell Mo model. PC vector spectra of L-shell Mo, including F, Ne, Na and Mg-like transitions are studied to investigate the polarization types of these transitions. PC1 vector spectra of F, Ne, Na and Mg-like transitions result in linear polarization of Stokes Q profiles. Besides, PC2 vector spectra show linear polarization of Stokes U profiles of 2p⁵3s of Ne-like transitions which are known as responsive to a magnetic field [Tr?bert, Beiersdorfer, and Crespo López-Urrutia, Nucl. Instrum Methods Phys. Res., Sect. B 408, 107–109 (2017)]. A 3D representation of PCA coefficients demonstrates that addition of an electron beam to the non-LTE model generates quantized, collective clusters which are translations of each other that follow V-shaped cascade trajectories, except for the case f = 0.0. The extracted principal coefficients are used as a database for an Artificial Neural Network (ANN) to estimate the plasma electron temperature, density and beam fractions of the time-integrated, spatially resolved L-shell Mo X-pinch plasma spectrum. PCA-based ANNs provide an advantage in reducing the network topology, with a more efficient backpropagation supervised learning algorithm. The modeled plasma electron temperature is about T_e ～ 660 eV and density n_e = 1 × 10²⁰ cm^?3, in the presence of the fraction of the beams with f ～ 0.1 and centered energy of 5 keV.