This article presents a simple and effective model-based sliding mode control strategy for robust temperature trajectory tracking of a batch reactor. With the process model being directly embedded in the controller formulation, the proposed sliding mode control scheme is a deterministic approach for which no statistical information of uncertainties is required and whose only assumption on uncertainties is that they are bounded. To show the convergence property as well as the robust stability of the resultant sliding mode control system, rigorous analysis involving the use of a Lyapunov approach is utilized. In addition, for use in an environment that lacks full-state measurements, a control scheme that integrates a sliding observer with the proposed sliding mode controller is suggested for batch process control. The effectiveness as well as the applicability of the proposed model-based sliding mode control scheme is demonstrated by considering the control of a batch reactor in the presence of plant/model mismatch, parameter variations, periodic disturbances, and measurement noises. Furthermore, as a basis for performance evaluation, comparisons between a model-based globally linearizing controller and a conventional sliding mode controller are performed systematically. Extensive simulation results reveal that the proposed sliding mode control strategy, though simple, is a very effective and promising approach for robust temperature trajectory tracking control of a batch reactor despite the wide range of operating conditions, nonlinear system dynamics, and the existence of diverse process uncertainties.