Prominence seismology aims to determine difficult to measure physical parameters in
prominence plasmas by a combination of observed and theoretical properties of waves
and oscillations. Current inversion techniques have been successful in the determination
of Alfvén travel times, magnetic field strengths, and density structuring, using fine
structure oscillations. Yet, the inference of difficult to measure parameters is not
an easy task. We propose the use of inversion techniques in the Bayesian framework,
which enables us to infer the most probable values of the relevant parameters compatible
with the observed wave properties, and to extract their confidence levels incorporating
observed uncertainties in a consistent manner. The technique is now being successfully
applied to coronal seismology. Examples are provided on its potential for the determination
of physical parameters in oscillating prominence fine structures. The method also enables
to perform model comparison to assess, e.g., the plausibility of alternative damping
mechanisms of prominence oscillations.