The area of Layered Space-Time (LST) systems has received enormous attention recently as they can provide a roughly linear increase in data rate by using Multiple Transmit and Receive antennas. The optimal detection strategy for a LST receiver is to perform a Maximum-Likelihood (ML) search over all possible transmitted symbol combinations has an exponential complexity when the constellation size of number of transmit antennas increase. While sub-optimal decoders, such as VBLAST, provide linear decoding only where the number of receive antennas is at least equal to the number of transmit antennas. The decoding scheme proposed in this paper, called Asterism decoding, looks for a more efficient way of finding the ML solution by first considering the case of multiple transmit antennas and a single receive antenna. The decoder is then extended to achieve ML like performance for any number of receive antennas. It further shows that Asterism decoding has at least an approximate order of magnitude reduction in computational complexity when compared to ML decoding. Asterism decoding is the first lower complexity decoder that achieves ML-like performance for systems where the number of receive antennas is less than the number of transmit antennas without the additional use of error coding.