Fatigue cracks have been one of the major factors for the deterioration of steel bridges. In order to maintain structural integrity, monitoring fatigue crack activities such as crack initiation and propagation is critical to prevent catastrophic failure of steel bridges due to the accumulation of fatigue damage. Measuring the strain change under cracking is an effective way of monitoring fatigue cracks. However, traditional strain sensors such as metal foil gauges are not able to capture crack development due to their small size, limited measurement range, and high failure rate under harsh environmental conditions. Recently, a newly developed soft elastomeric capacitive sensor has great promise to overcome these limitations. In this paper, crack detection capability of the capacitive sensor is demonstrated through Finite Element (FE) analysis. A nonlinear FE model of a standard ASTM compact tension specimen is created which is calibrated to experimental data to simulate its response under fatigue loading, with the goal to 1) depict the strain distribution of the specimen under the large area covered by the capacitive sensor due to cracking; 2) characterize the relationship between capacitance change and crack width; 3) quantify the minimum required resolution of data acquisition system for detecting the fatigue cracks. The minimum resolution serves as a basis for the development of a dedicated wireless data acquisition system for the capacitive strain sensor.