  We present an overview of recent works on the statistical description of
turbulent flows in terms of probability density functions (PDFs) in the
framework of the Lundgren-Monin-Novikov (LMN) hierarchy. Within this framework,
evolution equations for the PDFs are derived from the basic equations of fluid
motion. The closure problem arises either in terms of a coupling to multi-point
PDFs or in terms of conditional averages entering the evolution equations as
unknown functions. We mainly focus on the latter case and use data from direct
numerical simulations (DNS) to specify the unclosed terms. Apart from giving an
introduction into the basic analytical techniques, applications to
two-dimensional vorticity statistics, to the single-point velocity and
vorticity statistics of three-dimensional turbulence, to the temperature
statistics of Rayleigh-B\'enard convection and to Burgers turbulence are
discussed.
