  This paper investigates the problem of prediction of stellar parameters,
based on the star's electromagnetic spectrum. The knowledge of these parameters
permits to infer on the evolutionary state of the star. From a statistical
point of view, the spectra of different stars can be represented as functional
data. Therefore, a two-step procedure decomposing the spectra in a functional
basis combined with a regression method of prediction is proposed. We also use
a bootstrap methodology to build prediction intervals for the stellar
parameters. A practical application is also provided to illustrate the
numerical performance of our approach.
