The delay in climate action forces Carbon Dioxide Removal (CDR) or Negative Emissions Technologies (NETs) to become unavoidable. Different types of NETs (afforestation/reforestation, biochar application, soil carbon sequestration, bioenergy with carbon capture and storage, enhanced weathering, and direct air carbon capture and storage) have uncertain costs and performance that are difficult to predict precisely, a characteristic of unproven, emerging technologies. At the same time, the implementation of NETs will be subject to target negative emissions and resource constraints that lack precision. If unaddressed, these uncertainties will lead to techno-economic risks on the part of the stakeholder or decisionmaker. This study utilizes Fuzzy Mathematical Programming to optimize a NETs portfolio with uncertain performance and costs. The model gives the best compromising solution that maximizes the total negative emissions while conserving the resources. The performance of the model is demonstrated by case studies.