This paper presents three empirical approaches to forecasting inflation in Pakistan. The preferred approach is a leading indicators model, in which broad money growth and private sector credit growth help forecast inflation. A univariate approach also yields reasonable forecasts, but seems less suited to capturing turning-points. A vector autoregressive (VAR) model illustrates how monetary developments can be described by a Phillips-curve-type relationship. We deal with potential parameter instability on account of fundamental changes in Pakistan’s economic system by restricting our sample to more recent observations. Aspects of Gregorian and Islamic calendar seasonality are addressed by using 12-month moving averages.