The research paper provides a probabilistic study of free vibration for functionally graded material plates through an artificial neural network technique. The Latin hypercube sampling technique has been applied to train the ANN model. Monte Carlo simulation and the finite element methods is used to authenticate and verify the intended methodology for probabilistic natural frequency study of FGM plates. The Probabilistic variability of input factors namely density, modulus of elasticity, modulus of shear, Poisson ratio has been considered. The material parameters are calculated by utilizing the power law. The impact of different characteristics, such as temperature, power law exponent, twist angle and degree of variability on the initial three natural frequencies is evaluated. In contrast to the conventional Monte Carlo simulation, the suggested ANN model is highly computationally efficient. This ANN built finite element (FE) methodology can also be applied to other structural analyses involving complex geometries.