There is high clinical demand for the resolution of tendinopathies, which affect mainly adult individuals and animals. Tendon damage resolution during the adult lifetime is not as effective as in earlier stages where complete restoration of tendon structure and property occurs. However, the molecular mechanisms underlying tendon regeneration remain unknown, limiting the development of targeted therapies. The research aim was to draw a comparative map of molecules that control tenogenesis and to exploit systems biology to model their signaling cascades and physiological paths. Using current literature data on molecular interactions in early tendon development, species-specific data collections were created. Then, computational analysis was used to construct Tendon NETworks in which information flow and molecular links were traced, prioritized, and enriched. Species-specific Tendon NETworks generated a data-driven computational framework based on three operative levels and a stage-dependent set of molecules and interactions (embryo–fetal or prepubertal) responsible, respectively, for signaling differentiation and morphogenesis, shaping tendon transcriptional program and downstream modeling of its fibrillogenesis toward a mature tissue. The computational network enrichment unveiled a more complex hierarchical organization of molecule interactions assigning a central role to neuro and endocrine axes which are novel and only partially explored systems for tenogenesis. Overall, this study emphasizes the value of system biology in linking the currently available disjointed molecular data, by establishing the direction and priority of signaling flows. Simultaneously, computational enrichment was critical in revealing new nodes and pathways to watch out for in promoting biomedical advances in tendon healing and developing targeted therapeutic strategies to improve current clinical interventions.