Among European nations, Greece stands out as particularly vulnerable to fire activity. Given that most of fire events are caused, either directly or indirectly, to human-driven processes, socioeconomic conditions represent a promising dimension for improving fire risk management. Such conditions may shed light on the spatial and temporal patterns of fire distribution across the country. This study investigates the extent to which a range of socioeconomic factors and their temporal dynamics over the period 2000–2021 are associated with fire ignition frequency and the extent of burned land across Greece’s thirteen administrative Regions. Key socioeconomic variables examined include Gross Domestic Product (GDP), GDP per capita, employment levels within the agriculture and forestry sectors, and Gross Value Added (GVA). These factors were analyzed against fire history obtained by the Greek Fire Service database. To examine the influence of the socioeconomic factors, both correlation analysis and Loess nonparametric regression modeling were applied, enabling the identification of underlying trends between socioeconomic factors, fire occurrence and burned area at regional level. Findings across all thirteen Regions consistently demonstrate that the selected socioeconomic factors exhibit moderate but significant correlations and trends and may exert influence over fire frequency and burned area in the country. The variables that appeared to be correlated with variations in fire occurrence were GDP and GVA. Loess nonparametric regression revealed non-linear patterns across several regions, suggesting that the influence of socioeconomic factors on fire occurrence varies spatially and cannot be adequately described by a simple linear relationship. The results underscore the significance of socioeconomic factors in interpreting fire regimes in Greece and could be crucial in enabling fire management authorities to adapt fire prevention strategies that are appropriately tailored to the distinct socioeconomic, cultural, and ecological characteristics of each Region.