This paper presents a novel method for rolling element defect simulation for critical insights based on explicit finite element analysis using ANSYS to study the misalignment and imbalance with respect to time-domain spectrum obtained, and transform contact forces into the frequency domain via Fast Fourier Transform (FFT) in Python. The frequency spectrum obtained reveals defect characteristics. For the case to find rolling element defects exhibit high-frequency harmonics above 150 Hz. And for misalignment shows frequency harmonics ranges from 50 Hz with harmonics at 100 Hz. The last case of imbalance displays a 20 Hz frequency with sidebands. The study highlights the ability of advanced ML solutions for more accurate fault discovery in simulated systems, and real-time monitoring of the process, complements, and enhances accuracy, by expanding defect coverage. But it also contributes to the industrialization of nonlinear transient dynamic analysis. These findings emphasize the value of frequency analysis in Prognostics and Health Management.