Worst-case analysis is one of the most important elements in the verifica-tion and validation process used to ensure the reliable operation of safety-critical systems for defence, aerospace and space applications. In this the-sis, an optimization-based worst-case analysis framework is developed forspace applications. The proposed framework has been applied and success-fully validated on a number of European Space Agency funded researchprojects in the areas of flexible satellites, hypersonic re-entry vehicles, andautonomous rendezvous systems. Firstly, the problem of analyzing the robustness of an Attitude and OrbitalControl Systems (AOCS) for a flexible scientific satellite with a large num-ber of uncertainties is considered. The analysis employs a detailed simula-tion model of a flexible satellite and multivariable controller, together witha number of frequency and time domain performance criteria which arecommonly used by the space industry to verify correct functionality of full-authority multivariable satellite control systems. Second, the flying qualitiesanalysis of a re-entry vehicle is investigated for a number of complex sce-narios involving different types of uncertainties and disturbances. Specificmethods are utilized to deal with analysis problems involving probabilisticuncertainties, physically correlated uncertainties and highly dynamical dis-turbances. In another study, an integrated analytical/optimization-basedanalysis framework is proposed for the robustness analysis of AOCS fora telecoms satellite with flexible appendages. We develop detailed LinearFractional Transformation (LFT)-based models of the uncertainties presentin a modern telecom satellite and apply µ-analysis to these models in or-der to generate robustness guarantees. We validate these models and re-sults by cross-checking them against worst-case analysis results producedby global optimization algorithms applied to the original system model. Fi-nally, the optimization-based framework developed in this thesis is employedto analyze the robustness of the Guidance, Navigation and Control (GNC)system for autonomous spacecraft. This study considers the autonomousrendezvous problem over the terminal flight phase in the presence of a largenumber of realistic parametric uncertainties and a number of safety criteriarelated to the capture specification. An integrated analytical/optimization-based approach was also developed for this problem so that the computa-tional cost of simulation-based analyses can be reduced, through leveragingresults from robust control tools such asµ-analysis. The main contributions of the thesis are (a) to provide convincing demon-strations of the usefulness of optimization-based worst-case analysis on anumber of different space applications, each of which involves highly com-plex simulators developed by leading industrial companies from the Euro-pean Space sector, and (b) to show how optimization-based analysis meth-ods may be combined with analytical tools from robust control theory tocreate a more integrated, efficient and reliable verification and validationprocess for space applications.