The performance of Organic Rankine cycle (ORC) systems is defined by the system design as well as working fluid selection. Integrated thermo-economic optimisation of both can unlock maximum system potential in terms of power generation at a minimal cost. However, such optimisation is associated with uncertainties related to the underlying thermodynamic fluid models, ORC system models, and equipment cost correlations. In this paper, the main sources of uncertainty are quantified and their impact on optimal system design and working fluid selection is analysed. A computer-aided molecular and process design (CAMPD) optimisation framework based on first-law system design models is developed and validated with experimental data. Results reveal that the developed framework can identify promising working fluid candidates with high probabilities, even considering the most important sources of uncertainty. In a case study of industrial waste-heat utilisation, it was found that while uncertainties challenge the strict discrimination of the most promising working fluids, they mainly affect absolute performance values, rather than the overall ranking of working fluids. Propane was identified as having a 94-% probability of being among the best 3 working fluids. Furthermore, although the overall specific investment costs are highly uncertain (mean: 3,810 £/kW, standard deviation: 720 £/kW), the results are less sensitive to uncertainties in fluid equilibrium and transport properties (standard deviation: 160 £/kW), with the impact of equipment cost uncertainties being dominant. The analysis of uncertainties in working fluid selection also applies to other CAMPD problems, and other applications of group-contribution-based equations of state.