A small fraction of particles in the atmosphere can catalyze ice formation in cloud water drops through heterogeneous freezing nucleation at temperatures warmer than the homogeneous freezing temperature of approximately −38°C. The rate for heterogeneous freezing nucleation is dependent on several factors, including the type and surface area of dust that is immersed inside the drop. Although nucleation is an inherently stochastic process resulting from size fluctuations of the incipient ice germ, there is a growing body of literature that suggests that quasi-deterministic models of ice nucleation can describe laboratory experiments. Here we present new experiments and simulations that aim to better constrain theoretical models fitted to laboratory data. We collected ice nucleation data for Arizona Test Dust aerosol immersed in water using a droplet freezing assay setup that allows for the cooling rates to be changed between 10 and 0.01 K min−1. Discrete event simulations based on a variant of the multiple-component stochastic model of heterogeneous freezing nucleation were used to simulate different experimental procedures. The nucleation properties of the dust are specified by four material-dependent parameters that accurately describe the time dependence of the freezing process. We anticipate that the combination of discrete event simulations and a spectrum of experimental procedures described here can be used to design more meaningful laboratory experiments probing ice nucleation and will aid the development of better parameterizations for use in models.