Recent progress in macromolecular reaction engineering has enabled the synthesis of sequence-controlled polymers. The advent of olefin block copolymers (OBCs) via chain shuttling polymerization of ethylene with α-olefins has opened new horizons for the synthesis of polyolefins having a dual character of thermoplastics and elastomers. Nevertheless, the use of two catalysts with different comonomer selectivities and a chain shuttling agent, dragging and dropping live chains between active catalyst centers, made precise tailoring of OBCs microstructure containing hard and soft units a feasible challenge. This work discusses the possibility of predicting properties of OBCs from its simulated molecular patterns. The microstructural characteristics of OBCs are discussed in terms of topology-related and property-related features. An intelligent tool, which combines the benefits of kinetic Monte Carlo simulation and artificial neural network modeling, is used to explore the connection between polymerization recipe (catalyst composition, ethylene to 1-octene monomer ratio, and chain shuttling agent level) and topology-related as well as property-related microstructural features. The properties of target OBCs are reflected in the hard block percent, the number of 1-octene units in the copolymer chains, and the longest ethylene sequence length of the hard and soft segments.