This thesis is a critical examination of phenomenological nuclear mean field theories, focusing on reliable description of levels of individual particles. The approach presented here is new in the sense that it not only allows to predict the numerical values obtained with this formalism, but also yields an estimate of the probability distributions corresponding to the experimental results. We introduce the concept of ‘theoretical errors’ to estimate uncertainties in theoreticalmodels. We also introduce a subjective notion of ‘Predictive Power’ of nuclear Hamiltonians, which is analyzed in the context of the energy spectra of individual particles. The mathematical concept of ‘Inverse Problem’ is applied to a realistic mean-field Hamiltonian. This technique allows to predict the properties of a system from a limited number of data. To deepen our understanding of Inverse Problems, we focus on a simple mathematical problem. A function dependent on four free parameters is introduced in order to reproduce ‘experimental’ data. We study the behavior of the ‘fitted’ parameters, their correlation and the associated errors. This study helps us understand the importance of the correct formulation of the problem. It also shows the importance of including theoretical and experimental errors in the solution.
