The quality of welded joints is crucial in steel pipe manufacturing, as defects can lead to structural failure and reduced product reliability. Non-Destructive Testing (NDT) methods like Radiography Testing (RT) and Ultrasonic Testing (UT) are widely used for detecting weld defects but they face challenges such as radiation hazards and inefficiency in high-temperature environments. Magnetic Induction Tomography (MIT) has emerged as a safer, non-invasive alternative to overcome these limitations. This study evaluates the performance of MIT sensors in detecting surface and subsurface defects through Multiphysics simulations. The results demonstrate that MIT sensors can detect defects as small as 0.5 mm in diameter and differentiate sizes up to 5 mm, with optimal sensitivity achieved at 100 kHz, within a frequency range of 10 kHz to 1 GHz. The validation with experimental data confirmed the high precision of the MIT sensors in detecting axial and subsurface defects, demonstrating their ability to generate accurate imaging of weld defects. These findings highlight MIT’s potential to enhance the safety and efficiency of weld quality inspections. Further research is recommended to improve the sensor resolution to detect smaller and deeper defects, thereby enabling wider industrial adoption.