First known attempt to empirically modeling and experimentally verifying the growth of ilmenite single crystals using Czockralski process is presented. Czochralski is an industrial crystal pulling process extensively used for silicon and germanium single crystal growth. The experimental apparatus for ilmenite growth process has been significantly improved, and applied to acquisition of noise-free experimental data for empirical modeling. A feedforward multilayer perceptron is used to develop a single-step predictor, modeling the thermal response of the Czochralski single crystal growth process of ilmenite. The training of the neural network is performed using adaptive back-propagation, an accelerated learning algorithm.