The present paper concentrates on neural complexity generated during the phase transition in epileptic seizure. Epileptic seizures represent a sudden and transient change in the synchronized firing of neuronal brain ensembles. The proposed model treats the brain as an excitable medium for the propagation of waves of electrical activity with a level of abstraction encompassing underlying variables into a number of discrete states. The analysis presented here provides support for the notion of dynamical phase transition in the sequence of chaos --> complexity --> order during the progress of epilepsy. Evolving cellular automata and quantifying it using Langton parameter shows critical value or highest complexity at the onset of seizure phenomenon.