It is known that in the critical case the conditional least squares estimator (CLSE) of the offspring mean of a discrete time branching process with immigration is not asymptotically normal. If the offspring variance tends to zero, it is normal with normalization factor n 2 / 3 . We study a situation of its asymptotic normality in the case of non-degenerate offspring distribution for the process with time-dependent immigration, whose mean and variance vary regularly with non-negative exponents α and β , respectively. We prove that if β < 1 + 2 α , the CLSE is asymptotically normal with two different normalization factors and if β > 1 + 2 α , its limit distribution is not normal but can be expressed in terms of the distribution of certain functionals of the time-changed Wiener process. When β = 1 + 2 α the limit distribution depends on the behavior of the slowly varying parts of the mean and variance.