In this paper, the structure of the relationship between woody biomass energy consumption and real per Capita GDP was analyzed in the period of 1980–2012 for the selected African countries by ARDL (Autoregressive Distributed Lag), nonlinear ARDL, Granger causality and forecast error variance decomposition methods. After a symmetric relationship between woody biomass energy consumption and economic growth was determined by the nonlinear ARDL (NARDL) model, ARDL and Granger Causality methods were applied. According to results of the Granger Causality method, there is a unidirectional causality running from economic growth to woody biomass energy consumption for Botswana, Cameroon, Uganda, and Zambia and from woody biomass energy consumption to economic growth for Burkina Faso, Malawi, Central African Republic, Namibia, Côte d’Ivoire, Djibouti, Gabon and Zimbabwe. The bidirectional causality was supported for Kenya, Lesotho, Madagascar and Togo. Lastly, forecast error variance decomposition method was applied to support the results obtained from Granger Causality method. The forecast error variance decomposition results of real per Capita GDP and woody biomass energy consumption showed that woody biomass energy and real per Capita GDP made the important contribution to the forecast error variance of itself and each other.