Seismic travel‐time tomography, a common method for studying the Earth’s three‐dimensional seismic velocity variations, relies on robust measurement of seismic phase arrival times. Absolute arrival times are estimated by visually picking the emergence of the seismic phase of interest on seismograms. Subtracting theoretical arrival times (calculated using a known source location and origin time) from these picked absolute times yields absolute delay times. A widely used method whereby careful picking of absolute arrival times is not required is multi‐channel cross‐correlation (MCCC), developed by VanDecar and Crosson (1990). In MCCC, phase arrival times relative to an unknown average time are obtained by finding the maximum of the cross‐correlation function between each possible pair of seismograms. The preprocessing time of marking the phase to be cross‐correlated in MCCC has increased with the tremendous growth in seismic data volume over the past decade. In this paper, we introduce an efficient and robust computer tool, Automated and Interactive Measurement of Body‐wave Arrival Times (AIMBAT), to measure teleseismic body‐wave arrival times for phases for which arrival time predictions exist. The tool is based on MCCC, but an iterative cross‐correlation and stack (ICCS) algorithm replaces the initial phase marking part of the MCCC procedure, which significantly reduces the need for early user labor. The tool is written in Python (http://www.python.org) and utilizes its open‐source packages Numpy (http://numpy.scipy.org) and Scipy (http://scipy.org) for numerical array computation and Matplotlib (Hunter, 2007) for two‐dimensional plotting and graphical user interface (GUI) applications. We also transcribed the Fortran version of MCCC from VanDecar and Crosson (1990) into Python, which was validated by running both versions on the same data. Python is an efficient, high‐level, object‐oriented, and platform‐independent (Linux, Mac, and Windows) …