Circulating cooling water system (CCWS) is widely used in industry. Usually the relative optimisation problems are solved under determined values of input parameters. Once some parameters become uncertain, the system may not be optimal or stable. In a CCWS, the existence of these uncertainties will make the original optimal cooling network unreasonable, the design of pump is not suitable, and thus the entire system may no longer be safe. However, there is limited research on the synthesis of CCWS involving uncertainty, although they have been considered for some other process systems. This work presents a mathematical optimisation model for the design of CCWS under uncertainties. Uncertain parameters are described in the form of probability distribution functions. The models are formulated by chance constrained (CCP) methods, and they are solved by GAMS software. The objective is to determine the optimal network configuration that achieves the minimum total annualized cost. Meanwhile, the total circulating water flowrate and the heat transfer efficiency are optimised. To a certain extent, the system has operational stability and reliability. A modified industrial case study is solved to illustrate the proposed approach.