Porosity can form during investment casting as a result of the solidification conditions. Significant porosity can result in agglomerations (pore clusters) which are a primary crack initiation source and can result in reduced fatigue life of Nickel-based superalloys. Such clusters of porosity are today conventionally measured using 2D micrographs. An approach to accurately predict and analyze casting porosity from 2D cuts while facing in reality a 3D shape problem is currently missing. In this work, an approach that combines automation and simulation to assess the representative pore dimension, their interconnectivity and the porosity position is presented. On a LPT blade made of IN100, the porosity percentage and Feret diameter have been measured in multiple cuts and the porosity was found to be in the range of 0.88 to 5.4 pct. From the same micrographs the critical defect sizes were estimated with an automated tool to be in the range of 200 to 1800 $$\mu$$ μ m. The simulated shrinkage porosity for the same part, was predicted to be in the range of 1.67 to 2.33 pct. This study shows that the scaling factor between the pore Feret diameter and the critical pore size is equal to 2.9, in accordance to the proportionality of critical pores size clusters calculated from a 2D and 3D dataset. Finally, the simulated casting porosity was compared to that measured on cast blades in critical regions and the predictive accuracy is discussed in detail.