Corporate Real Estate (CRE) investors are often confronted with a need for flexibility in buildings. They often embark on costly renovations to accommodate changing use requirements. When new needs arise, landlords and tenants often risk loss due to inability to easily switch to configurations that can meet those needs. The main cause for this problem is lack of a planning model that can allow buildings to easily evolve over time allowing decision-makers to hedge investment positions against risk due to uncertainty. The emergence of Real Options (RO) theory in the 1970's has led to debates in search of a better planning model for real projects. The success of RO application in building construction (BC) hinges on the development of models that can be used to assess economic performance of flexible design options (FDO) in building systems. For building interior spaces, there is currently no model that can value flexibility of partition systems. The purpose of this study is to present a model that can be used to value flexibility in mutually exclusive partition systems over a project's life span. The proposed model uses decision tree representation, stochastic forecasting and random sampling of decision-path scenarios to generate cumulative risk profiles of partition systems' life cycle costs with expected median value, standard deviation and variance to inform decision making under uncertainty. The research processes include: assumptions, decision-making structure for identification of uncertain variable, model representation, spreadsheet programming, Monte Carlo simulation, and validation. The model will enable application of RO "in" BC projects.