Existing justifications for applying the bootstrap to linear regressions rely on the asymptotic properties of the estimates, as the parent sample size increases indefinitely, and on the evidence from Monte Carlo experiments. In this paper, the properties of various bootstrap regression estimates are developed, as the number of bootstrap replications increases indefinitely, the sample size remaining fixed and finite. Various theoretical results that serve to reinforce results previously obtained only from Monte Carlo experimentation are obtained.