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Joint communications and sensing (JCAS) is envisioned as a key feature in future wireless communications networks. In massive MIMO-JCAS systems, the very large number of antennas causes excessively high computational complexity in beamforming designs. In this work, we investigate a low-complexity massive multiple-input-multiple-output (MIMO)-JCAS system employing the maximum-ratio transmission (MRT) scheme for both communications and sensing. We first derive closed-form expressions for the achievable communications rate and Cram´er–Rao bound (CRB) as functions of the large-scale fading channel coefficients. Then, we develop a power allocation strategy based on successive convex approximation to maximize the communications sum rate while guaranteeing the CRB constraint and transmit power budget. Our analysis shows that the introduction of sensing functionality increases the beamforming uncertainty and inter-user interference on the communications side. However, these factors can be mitigated by deploying a very large number of antennas. The numerical results verify our findings and demonstrate the power allocation efficiency.