  Nuclear pasta, that is an inhomogeneous distribution of nuclear matter
characterised by non-spherical clustered structures, is expected to occur in a
narrow spatial region at the bottom of the inner crust of neutron stars, but
the width of the pasta layer is strongly model dependent. In the framework of a
compressible liquid-drop model, we use Bayesian inference to analyse the
constraints on the sub-saturation energy functional and surface tension imposed
by both ab-initio chiral perturbation theory calculations and experimental
measurements of nuclear masses. The posterior models are used to obtain general
predictions for the crust-pasta and pasta-core transition with controlled
uncertainties. A correlation study allows extracting the most influential
parameters for the calculation of the pasta phases. The important role of
high-order empirical parameters and the surface tension is underlined.
