This essay delves into the mathematical exploration of musical tones through the application of Fourier Transformation, a pivotal tool in the field of digital signal processing and acoustics. By converting complex musical tones from the time domain to the frequency domain, Fourier Transformation enables the deconstruction of sounds into their constituent frequencies, revealing the unique harmonic structures that contribute to the characteristic timbre of different musical instruments. The focus of this analysis is particularly on the trumpet, chosen for its rich harmonic content and distinctive sound. Through the examination of audio recordings, this study uncovers the fundamental frequency and harmonics of the trumpet, demonstrating how these elements combine to form its unique acoustic fingerprint. The process involves recording, analyzing, and comparing musical tones using software tools like MATLAB and Python, providing an accessible yet profound insight into the intersection of mathematics and music. This essay not only highlights the technical methodology of Fourier Transformation in analyzing musical tones but also explores its practical applications in music theory, digital audio processing, and the broader field of acoustics. The findings underscore the transformative power of mathematical analysis in understanding and appreciating the complex beauty of musical sounds, opening avenues for further research and application in both the scientific and artistic domains.