Over the last decade, metronomic chemotherapy has been increasingly considered as an attractive strategy for treating cancer in a variety of settings. Beside pharmaco-economic considerations making metronomics a unique opportunity in low- or middle-income countries, revisiting dosing schedules using continuous low doses of cytotoxics should theoretically permit to reduce the incidence of treatment-related toxicities, while offering unexpected novel mechanisms of actions such as antiangiogenic or immuno-stimulating properties. Consequently, a number of clinical trials sought to evaluate to what extent switching to metronomic schedules could actually impact indeed on the efficacy/toxicity balance of a variety of anticancer drugs in both adults and pediatric oncology. Vinorelbine is a vinca-alcaloïd that remains the backbone of several regimens to treat patients with metastatic breast cancer or non-small cell lung cancer. Additionally, vinorelbine is widely used to treat a variety of solid tumors in children such as rhabdomyosarcomas and acute leukemia. The recent approval of an oral formulation of vinorelbine has open the way to developing alternative metronomic schedules with this drug. Consequently, a number of clinical trials investigating on metronomic vinorelbine have been performed over the last few years, with seemingly inconsistent results to date. Of note, all the studies published thus far were based upon empirical determination of the metronomic schedule, both in terms of doses, drug-free intervals and repartition of the administrations throughout time. Because the very concept of «low, repeated doses with little or no drug-free interval» covers numerous possible combinations, determining the optimal protocol using traditional under-powered empirical design looks like an unreachable goal. In this context, mathematical modeling offers invaluable in silico tools to help determining the optimal metronomic schedule among a variety of possibilities. This review covers the latest clinical trials investigating on metronomic vinorelbine and proposes alternative strategies for developing computational decision support to make metronomics a scientific-grounded strategy, rather than an empirical practice at the bedside. In particular, mathematical simulations using an original pharmacokinetics/pharmacodynamics constraint models provide clues for exploring new paths in the way metronomic vinorelbine could be scheduled in patients with lung cancer.