The generalized Kaiser–Bessel window function is defined via the modified Bessel function of the first kind and arises frequently in tomographic image reconstruction. In this talk,I will present in details the properties of the Kaiser–Bessel distribution, which is defined via the symmetric form of the generalized Kaiser–Bessel window function. The Kaiser–Bessel distribution resemble sto the Bessel distribution of McKay of the first type, it is a platykurtic or sub-Gaussian distribution,it is not infinitely divisible in the classical sense and it is an extension of the Wigner’s semicircle,parabolic and n-sphere distributions, as well as of the ultra-spherical (or hyper-spherical) andpower semicircle distributions. I will deduce the moments and absolute moments of this distribution and found its characteristic and moment generating function in two different ways. In addition, I show its cumulative distribution function in three different ways and deduce a recurrence relation for the moments and absolute moments. Moreover, by using a formula of Ismail and May on quotient of modified Bessel functions of the first kind, I deduce a closed-form expression for the differential entropy. Finally, I also present a modified method of moments to estimate the parameters of the Kaiser–Bessel distribution, and by using the classical rejection method I present two algorithms for sampling independent continuous random variables of Kaiser–Besseldistribution. This talk is based on a joint work with Tibor Pogany and an earlier version of this talk can be found at https://www.youtube.com/watch?v=SElYk9xd500.