Computational modeling is now generally accepted as an essential procedure for the dynamic analysis of chemical processes. Many of these processes are distributed parameter systems, i.e., systems in which state variables depend on several independent variables (such as time and space) and which are described by sets of nonlinear partial differential equations (PDEs). The method of lines (MOL) is probably the most widely used approach to the solution of evolutionary PDEs, and the objective of this paper is to report on the development of a Matlab-based MOL toolbox. The toolbox contains a set of linear spatial approximation techniques, e.g., finite-difference methods, implemented using the concept of differentiation matrices, as well as a set of nonlinear spatial approximations, e.g., flux limiters. In addition, several time integrators, including basic explicit methods and some advanced linearly implicit methods, are included. The underlying philosophy of these developments is to provide the user with a variety of easily understood methods and a collection of application examples that can be used as Matlab templates for the rapid prototyping of new dynamic simulation codes. In this paper, Burgers' equation in one and two space dimensions, as well as a dynamic model of a three-zone tubular fixed-bed reactor used for studying benzene hydrogenation, and the poisoning kinetics of thiophene on a nickel catalyst are considered.