In the demographic, actuarial, and economic fields, projections and forecasts provide valuable insights into the future evolution of death rates, population growth, and age distributions. Population projections and forecasts result from a comprehensive integration of migration flows, death rates, and birth rates over a given population stock. These figures furnish information on the size, age, and gender compositions of the entire population, as well as specific subgroups defined through conditioning on other variables of interest, such as income. Understanding mortality and population dynamics equips economic and social agents with tools for planning and decision-making across social, insurance, and health dimensions, to name a few. This work employs an extensive dataset comprising 533 million microdata entries from the Spanish population between 2010 and 2019, covering information on population stock, deaths, migrants, and births, with spatial markers at the highest level of territorial disaggregation—census sections. The aim of this study is to project the mortality dynamics of the Spanish population across four income levels, determined after splitting people according to the average income of their census section of residence. We achieve this by applying stochastic mortality projection models to the smoothed realized series, selecting the three established death forecasting models that best align with the statistical properties of our data.