Accurate population data is crucial for governments when formulating policies and tracking national development plans. In the Latin America and Caribbean (LAC) region, countries typically conduct national population and housing censuses every ten years, with intercensal periods filled by population projections and occasional intercensal counts. To maintain up-to-date population information, statistical models are employed to estimate population figures, particularly useful during intercensal periods or following significant events like natural disasters or migration. These estimates can also complement census data by highlighting potential omissions or overcounts. However, population censuses in the LAC region often encounter challenges in enumerating all households and individuals due to issues like planning, accessibility, or security problems in specific areas. Post-census evaluation tools help estimate final coverage and assess data quality, identifying errors and offering corrections. Statistical population models play a crucial role in evaluating census quality and coverage, yielding robust estimates at both national and subnational levels, ultimately contributing to improved census data accuracy in the region.