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The radiation belts of the Earth and other magnetized planets are populated by relativistic particles which are highly dynamic due to various source and loss processes. Although the Earth's intrinsic magnetic fields trap charged particles, the satellite observations revealed that the outer radiation belt fluxes are strongly affected by solar wind and geomagnetic activities. The direct drivers of the radiation belt variability are radial diffusion due to ultra-low frequency waves, and local wave-particle interactions due to whistler-mode waves, electron cyclotron waves and ion cyclotron waves. Quasilinear and nonlinear theories were developed to demonstrate and quantify the importance of each process in the radiation belt dynamics. Numerical simulations generally reproduce the overall source and loss of radiation belt particles, but detailed quantification of the observed features is challenging. Machine learning technique is proved as a useful tool in reproducing and forecasting the particle fluxes in radiation belts.