This chapter elucidates liquidity forecasting within the context of technical assistance. The audience for this chapter is central bank staff with a strong quantitative background. Liquidity forecasting entails a process of estimating the near-term path of a bank’s reserves using a centralized framework. Short-term liquidity forecasts are used to calibrate the volume of central bank monetary operations to align liquidity with the announced stance of monetary policy, whether expressed as an interest rate or as a quantity. The best practice would be for the central bank to receive accurate information for counterparties that have accounts in its books, including its monetary counterparties (banks) or non-monetary counterparties, such as the government. However, the central bank may not have direct access to some counterparties (e.g., the public which demands banknotes) or the information could include significant errors. This chapter presents the statistical methods that have been used in technical assistance to forecast liquidity factors and the demand for liquidity. It also proposes solutions to select the best models, measure forecast accuracy, and reconcile forecasts. Some liquidity factors are relatively easy to forecast due to regular patterns (currency in circulation) while others require more sophisticated models, such as the government account. There is a tradeoff between the cost of implementing complex models and the accuracy gains.