•The stochastic nonlinearities are firstly taken into account in fusion estimation.•A new approach is proposed to transform the multi-rate system into single-rate one.•The filters designed minimize the upper bound of the filtering error covariance.•A new CI-based fusion estimation scheme is proposed. This paper is concerned with the event-triggered robust fusion estimation problem for uncertain multi-rate sampled-data systems with stochastic nonlinearities and the colored measurement noises. Due to the effects of stochastic nonlinearities and parameter uncertainties, a new augmentation approach is proposed by which the multi-rate sampled-data system under consideration is transformed into the single-rate system. In order to eliminate the effect of the colored measurement noises, a measurement model with uncorrected noises is established. Based on the measurement model established, a set of local event-triggered filters is constructed and the upper bounds of the local filtering error covariances at each sampling instant are obtained. By using the Lagrange multiplier method, the local filter parameters are designed such that the upper bound obtained is minimum. For the local state estimates, a new fusion estimation scheme is proposed with the help of covariance intersection (CI) method and the consistency of the proposed CI-based fusion estimation scheme is shown. Finally, an illustrative example is presented to verify the effectiveness of the fusion estimation scheme proposed.