This paper presents a novel approach to the evaluation of nuclear data (ND), combining experimental data for thermal cross sections with resonance parameters and nuclear reaction modeling. The method involves sampling of various uncertain parameters, in particular uncertain components in experimental setups, and provides extensive covariance information, including consistent cross-channel correlations over the whole energy spectrum. The method is developed for, and applied to, 59 Ni, but may be used as a whole, or in part, for other nuclides. 59 Ni is particularly interesting since a substantial amount of 59 Ni is produced in thermal nuclear reactors by neutron capture in 58 Ni and since it has a non-threshold (n,α) cross section. Therefore, 59 Ni gives a very important contribution to the helium production in stainless steel in a thermal reactor. However, current evaluated ND libraries contain old information for 59 Ni, without any uncertainty information. The work includes a study of thermal cross section experiments and a novel combination of this experimental information, giving the full multivariate distribution of the thermal cross sections. In particular, the thermal (n,α) cross section is found to be (12.7 ± .7) b. This is consistent with, but yet different from, current established values.Further, the distribution of thermal cross sections is combined with reported resonance parameters, and with TENDL-2015 data, to provide full random ENDF files; all this is done in a novel way, keeping uncertainties and correlations in mind. The random files are also condensed into one single ENDF file with covariance information, which is now part of a beta version of JEFF 3.3.Finally, the random ENDF files have been processed and used in an MCNP model to study the helium production in stainless steel. The increase in the (n,α) rate due to 59 Ni compared to fresh stainless steel is found to be a factor of 5.2 at a certain time in the reactor vessel, with a relative uncertainty due to the 59 Ni data of 5.4 %.