This chapter reviews the literature on crude oil price forecasting. Specifically, we summarize alternative forecasting targets, existing predictive variables, and forecasting models that improve the accuracy of crude oil price predictions. Additionally, we analyze commonly used benchmark models and evaluation indicators for out-of-sample crude oil price forecasting. Our empirical application is based on the latest data and focuses on forecasting out-of-sample West Texas Intermediate average price returns. The results indicate that (i) technical indicators outperform macroeconomic variables in predictive power; (ii) advanced forecasting models enhance the predictability of crude oil prices; and (iii) the forecasting power of predictors and models is primarily concentrated in the short term and during periods of economic recession. The predictability of crude oil prices holds significant implications for government agencies, relevant industries, and investors.