This article provides a novel method to estimate historical population development. We review the previous literature on historical population time series estimates and propose a general outline to address the well-known methodological problems. We use a Bayesian hierarchical time series model that allows us to integrate parish level dataset and prior population information in a coherent manner. The procedure provides us with model-based posterior intervals for the final population estimates. We demonstrate its applicability by estimating long-term Finnish population development from 1647 onwards. This puts Finland among the very few countries with an annual population series of this length available.