In order to achieve maximum reflectivity of fiber Bragg grating (FBG), we simulate the behavior of FBG using application of feed-forward network of artificial neural network (ANN). In fiber optics communication, FBG is widely used in the field of optical fiber sensors and light wave communication based on the presence of photosensitivity in silicon fibers and optical waveguides. In previous studies, effect of modulation depth, grating length and change in refractive index have been studied. In this work, we include combination of various parameters like core radius, index difference, effective refractive index, grating length and index amplitude of grating and simulate using ANN. Minimized mean square error and linear regression have been achieved with different possible combinations of various parameters as input vectors to ANN. Studies show that ANN gives high performance results.