Bearing health monitoring is crucial for ensuring the reliability and longevity of machinery in various industries. This work presents a comprehensive method for assessing the condition of rolling element bearings through the development of a MATLAB-based graphical user interface (GUI). The GUI serves as an interactive analytical tool, allowing users to simulate and analyze a range of bearing faults, including outer race defects, inner race faults, ball irregularities, and cage anomalies. The analysis is conducted using both time-domain and frequency-domain methods. Time-domain analysis provides insights into the temporal behavior of vibration signals, while frequency-domain analysis, facilitated by Fast Fourier Transform (FFT) techniques, identifies characteristic frequencies associated with specific bearing faults. The combination of these approaches enhances the accuracy and reliability of fault detection. The GUI offers a user-friendly platform that allows maintenance engineers and machinery operators to experiment with various fault conditions and operating parameters. By simulating fault scenarios, users can gain valuable insights into potential issues, enabling the implementation of proactive maintenance strategies. This research contributes to the field of fault classification in rolling element bearings, helping to minimize downtime, reduce operational costs, and optimize the performance of precision machinery.