This document presents a partition method for minimizing deterministic finite automata (DFAs). It begins with background on DFAs and the goal of minimization. The proposed algorithm partitions the DFA states based on a formula, merges any equivalent states within each partition, and repeats until all states are processed. It applies the algorithm to a sample DFA using a tool, successfully minimizing it while preserving language recognition. The conclusion states the partition method allows merging equivalent states to minimize the DFA. Experiments showed no change to structure or accepted language after minimization.