A reliable farm decision model is becoming increasingly important, particularly in countries highly vulnerable to adverse climate change impacts. In this paper, social network analysis and ethnographic information were combined to map weather and climate information networks of rice and corn farmers in Oriental Mindoro, Philippines. Snowball sampling generated the network data locating the otherwise hidden population. Most of the respondents source their information from television. The topmost information that is accessible and used by rice farmers is on tropical cyclones, while corn farmers seek information about the wet and dry seasons. Despite the seemingly autonomous decision-making among farmers, there are nodal farmers in the networks whose reach can potentially influence their peers and improve the delivery of weather and climate information. These identified farmers either occupy a local leadership position or are members of farmers’ organizations. Predominantly, they have been farming for at least 25 years. These farmers can serve as ‘bridges’ to other farmers who are isolated or peripheral in the network by connecting them to the core’s primary contacts. Capacitating these potentially influential farmers could further improve the flow of weather and climate information, and better serve the farmers beyond the reach of agricultural extension services. Moreover, farmers’ experience of precarity, pressures them to take risks despite unfavorable forecasts and advisories. Climate studies and farm decision modeling should not leave out these narratives on agricultural precarities to understand the complexity of the effects of climate variability in agriculture.