Power system frequency serves as a real-time indicator of generation–load balance, system stability, and power quality, and its accurate estimation is critical for protection coordination, islanding detection, and ancillary‐service activation in modern distribution networks. Looking ahead, distribution grids face unprecedented challenges—high inverter penetration, reduced inertia, multi-frequency phenomena, large data centers, and nonstationary, unbalanced conditions—that demand novel paradigms in frequency analytics. This chapter presents a chronological survey of frequency‐estimation methodologies—from early zero‐crossing and electromechanical meters through spectral discrete Fourier transform based techniques, Prony and least‐squares fitting, and digital phase‐locked loops, to adaptive filters, advanced notch filters, and Kalman‐filter observers. Each class of algorithm’s underlying principles, dynamic performance, and implementation trade-offs are analyzed, highlighting their historical impact on microprocessor‐based protection relays, synchrophasor standards (IEEE C37.118), and real-time wide‐area monitoring. The chapter also explores recent advances such as interpolated discrete Fourier transform, dictionary-based dynamic phasor estimation, cooperative distributed filtering, and machine‐learning-augmented observers.