This study presents the first spectral analysis of long-term sea level variability in the Black Sea, aiming to identify dominant periodic components and explore their potential links to major oceanic climatic phenomena. Using daily sea level data spanning several decades, the Fast Fourier Transform (FFT) was applied to detect significant frequency patterns. The analysis revealed a 12.19-year cycle potentially related to the solar cycle, an 8.13-year cycle likely linked to variations in the North Atlantic Oscillation (NAO), and a 6.10-year cycle that may reflect the influence of the Pacific Decadal Oscillation (PDO). A 4.88-year signal possibly associated with the El Niño-Southern Oscillation (ENSO), along with a strong 1.02-year annual cycle, was also identified. These findings provide novel insights into the periodic nature of sea level changes in the Black Sea and demonstrate, for the first time, their connection with global-scale ocean-atmosphere variability.