Here I deal with data given on a uniform 3-D mesh (or 1-D or 2-D). I provide code for recovering missing data in the interior of the cube or abutting one wall of the 3-D data cube by a two-stage linear least squares process. First I fit a 3-D prediction-error filter (PEF) to the extended cube ignoring regression equations that involve missing elements. Then I estimate those missing elements by finding the data that minimizes the power out of the PEF. As in my other work since SEP-73, the volume can be broken into subcubes in which separate problems are solved and pieced together.