This study aims to create a model that predicts the year of immigration for people in Brazil and South Africa using cross-sectional microdata and ordinary least squares regression. Variables like gender, education, marital status, birthplace, age, and spousal characteristics are used to estimate immigration year. The results show that the model overestimates immigration years in both countries. Improving the model would require including more variables or using a different econometric method than OLS. This research represents early work on cohort analysis pioneered by George Borjas to more accurately estimate immigration trends.