The naval ship concept design process often embraces novel concepts and technologies that carry with them an inherent risk of failure simply because their application is the first of its kind. Failure is recognized by gaps between actual and required measures of performance, exceeded budgets, and late deliveries. These risks can be defined and quantified as the product of the probability of an occurrence of failure and a measure of the consequence of that failure. Since the objective of engineering is to design and build things to meet requirements, within budget, and on schedule the first time, it is important to consider risk, along with cost and performance, in trade assessments and technology selections made during concept design. To this end, this thesis presents a simplified metric and methodology for measuring the risk of ship design concepts as part of a Multi-Objective Optimization tool for naval ship concept design. The purpose of this tool is to provide a consistent format and methodology for multi- objective decisions based on dissimilar objective attributes, specifically effectiveness, cost and risk. This approach provides a more efficient and robust method to search the design space for optimal concepts than the traditional "ad hoc" naval ship concept design process where selection and assessment are often based on experience, design lanes, rules-of-thumb and Imagineering. This thesis begins with fue results of a literature and information search that investigates and describes risk, engineering systems safety, and state of the art risk analysis techniques currently in practice. Based on this background, a simplified metric and methodology is developed to calculate, quantify, and compare relative overall risk in a naval ship design optimization. To demonstrate this method, a naval ship risk register is developed for a notional ship design. This register identifies potential cost, performance, and schedule risk issues. Risk item descriptions are further defined as a function ofthe design parameters (DPs) considered for the notional ship. Risk Factors (RF) are calculated for each risk item based on fue DP selection. Each RF is the product of a Probability of Failure Occurrence (PF) and Potential Consequence of Failure (CF). An Overall Measure of Risk (OMOR) function is developed to measure the level of overall risk for a single concept design based on DP selections. A ship design case study is performed incorporating the OMOR function and risk items into a ship synthesis model capable of calculating cost, performance, and effectiveness. This case study uses a Multi-Objective Genetic Optimization (MOGO) to identify and define a series of non-dominated cost-effectiveness frontiers for a range of risk (OMOR) values. This new method for ship design optimization provides a novel approach and consistent format for multi-objective decision-making based on three dissimilar objective attributes: effectiveness, cost, and risk.