Error-correcting codes are very important in modern digital communication and data storage. They help make sure that data sent through noisy channels (like wireless networks or storage devices) arrives correctly, even if some bits get changed by interference or faults. This research uses Galois Theory, an area that studies finite fields (also called Galois fields) to improve how these codes work. Finite fields provide the rules for doing math with a limited number of numbers, which is perfect for building codes that can find and fix errors. This paper focuses on Bose–Chaudhuri–Hocquenghem (BCH) codes which are very good at fixing scattered random errors, used in flash memory and satellite communication. The research explains how Galois Theory helps: Represent messages as polynomials in finite fields: add extra information (redundancy) using special polynomials; Detect errors quickly with simple calculations called syndromes; and correct errors by solving equations over finite fields. Special attention is given to how field extensions, minimal polynomials, and field automorphisms (symmetries in finite fields) make these codes strong and reliable. We also shows how abstract mathematics from Galois theory turns into practical tools that fix errors in real-world systems, connecting pure mathematics to everyday applications like phones, computers, and space missions. This work aims to provide a clear understanding of why these classical codes remain effective and how Galois Theory continues to help solve modern data reliability problems.