The concentration of glucose in sweat recently has been measured with high sensitivity, selectivity, and reproducibility by nanostructured NiO electrodes manufactured by the glancing angle deposition (GLAD) technique. The GLAD technique allows electrode morphological properties such as porosity and film thickness to be tightly controlled, providing ample opportunity to enhance the sensor performance. Currently, the selection of optimal GLAD parameters is determined experimentally by trial and error, at high costs in time and resources. Numerical simulation allows the effects of various parameters on sensor performance to be investigated at a much lower cost compared to experimental studies. In this work, a 2D reaction–diffusion model for the surface-catalyzed reactions in the nanostructured GLAD electrodes is developed, which are then solved using the finite element method. Parametric studies on the nanocolumn thickness and nanocolumn separation of the GLAD structures are then conducted to optimize GLAD-based electrode structures with different adsorption and catalytic rates. This research offers new guidance for rapidly designing highly effective sensors with higher sensitivity and lower limits of detection.