For a long time now, social networks have been hailed for lowering otherwise high information and search cost to agents as well as making a principal’s market dominance increasingly ample. We therefore use the data from the 2016 FinAccess Household Survey for Kenya to unravel the effects of family networks in increasing the probabilities of members accessing microcredit. Broadly, we seek to verify whether family networks impact loan uptake by members of households and how this effect differ across gender. Employing the limited dependent variable modelling in our analysis, we find that family networks are vital in reducing search and information costs. Active networks increase the probability of accessing credit compared to non-active networks. This effect is more pronounced among women thus been in tandem with literature on determinants of credit access by women. Keywords: Social Networks, Credit Access.