The research aims the development of knitted reinforcement structures for inducing self-diagnostic properties into knitted reinforced composites for structural health monitoring. Conductive carbon fiber was used in knitted inlaid structures as inlay yarns, and l × 1 Rib knitted base fabric of polyester filament yarn was used for knitting. The reinforcement’s conductive nature induced self-diagnostic properties into composites using correlation of mechanical damages and changes in electrical resistance values. Single and double stimuli layers and inlay patterns of 3 × 1, 6 × 1 and 9 × 1 was used to check their impact on self-diagnostic properties. Mechanical testing and real-time electrical resistance monitoring proved knitted structures as a solution to induce self-diagnostic properties into composite materials. Composites having double stimuli (conductive) layers exhibited better self-diagnostic properties than single stimuli layer composites, and the self-diagnostic properties also improved as the inlay pattern of reinforcement moved from 9 × 1 to 6 × 1 and 3 × 1 inlay. Such knitted reinforced self-diagnostic composites could be practically used in structural health monitoring applications, e.g., complicated structures of large buildings infrastructures and machinery which require record of each minor happening with structures to keep smooth and successful running of the system.