Electrical Capacitance Tomography (ECT) is a promising non-invasive imaging technique with potential applications in agriculture, particularly for assessing tree health. This study explores the modeling and simulation of an ECT sensor tailored for detecting agarwood, a highly valued aromatic wood. The objective is to develop a finite element model using COMSOL Multiphysics, featuring an array of eight electrodes arranged in a two-dimensional configuration. The sensor’s performance is evaluated through simulations based on basic and complex geometric shapes, aiming to detect capacitance variations indicative of agarwood presence. Results are presented graphically, demonstrating the sensor’s capability to differentiate between agarwood and non-agarwood regions. The graph shows that sample A closely follows the baseline (no agarwood), indicating minimal distortion, while Ssample C exhibits slightly more variation, suggesting a higher presence or uneven distribution of agarwood. The sensor was also able to identify the complex agarwood shapes. These findings highlight the potential of ECT as a diagnostic tool for non-destructive testing in forestry, offering a foundation for future advancements in the non-invasive inspection of valuable tree species. Further refinement of the sensor design is recommended to enhance sensitivity and accuracy, with future work exploring different shapes and configurations, including tomographic imaging, to improve detection capabilities.