Risk is a defining feature of Australian dryland agriculture, with Australian farmers experiencing a much higher level of financial risk than any other developed country. This research shows that this high level of risk significantly impacts the financial viability of Australian farms. There is clear evidence which shows that farm business margins are declining, due to productivity growth rates lagging current rates of input cost inflation, a situation which has been exacerbated by a decade of extreme drought. Consequently Australian farmers are experiencing difficulty financing record levels of debt from earnings. Consequently novel management systems, incorporating appropriate levels of resilience, are critical to the future growth of the industry. This thesis describes the design, development and testing of a simulation model (the sequential multi-variate analysis, or SMA system) which offers a practical method of developing these systems and which is capable of : * quantifying the financial risks faced by individual farm businesses. * simulating the effects of strategic variations to management in a wide range of regions, using long-run sequenced rainfall and commodity prices, and * quantifying the impact of policy decisions on farm financial performance under conditions of historical or forecast risk, an outcome with significant implications for all levels of management in the Australian broadacre farming industry. The SMA system is shown to have the potential to become a practical and useful aid to all levels of farm management practice and policy. The results from a range of case studies suggest that current best-practice management systems, developed using current static methods of financial analysis, may be inappropriate and result in farmers adopting systems with unacceptable levels of financial risk, which yield sub-optimal financial returns. These analyses clearly show that farm viability depends more on minimising losses than maximising production, and it is these accumulated losses which threaten farm business survival and growth.