Surfactant micelles are self-assembled aggregates of surfactant molecules at the nanoscale that are formed at a surfactant concentration higher than a certain critical value, the critical micelle concentration (CMC). Micellar aggregate characterization is of industrial relevance in many fields such as pharmaceuticals, food science, nanotechnology and enhanced oil recovery, owing to their ability to dissolve hydrophobic materials, stabilize colloidal dispersions, and serve as nanocarriers or nanoreactors. The understanding of their physicochemical properties and structural characteristics is crucial to enhance their performances in specific applications. This chapter provides a general overview of the principles of micelle formation and the wide range of analytical techniques employed for their characterization. The most significant governing parameters like temperature, pH, electrolyte concentration, and molecular structure of surfactants are discussed in terms of size, shape, and stability of micelles. Treatment of spectroscopic techniques like UV-Visible, fluorescence, NMR, and FTIR spectroscopy shows that molecular interactions and micellar surroundings can be studied. Interfacial and surface tension methods like Wilhelmy plate, Du Noüy ring, pendant drop and bubble pressure technique are highlighted due to their ability to determine CMC and surface parameters. Thermal techniques like isothermal titration calorimetry (ITC), differential scanning calorimetry (DSC), and thermogravimetric analysis (TGA) provide more insight into the thermodynamics and stability of micelles. Electrochemical methods like zeta potential measurement, conductivity, and electrochemical impedance spectroscopy (EIS) are referred to for the determination of charge properties and interfacial behaviour. Scattering methods (SAXS, SANS, DLS), advanced microscopy (TEM, AFM, Cryo-EM), and computer simulations (MD, MC, DFT) are referred to as the tools for structural and dynamics studies. Case studies concerning drug delivery, nanoparticle stabilization, and nanoreactor applications and the recent challenges and future perspectives like; on time monitoring and AI-enabled analysis are discussed. The overall approach emphasizes on selecting appropriate methods for monitoring specific research or industrial goals.