Transformers are major equipment in a power system. Their reliability does not only affect the electric energy availability within a supplied area, but also the economical operation of a utility. Many power utilities in the world including Malaysia have distribution transformers that have been in operations for over 30 years. Aged distribution transformer will have higher risk of unexpected failure which will increase the operational cost. Nevertheless, the occurrence of transformer failure can be predicted based on historical events. In this research work, 2-Parameter Weibull distribution is used to model distribution transformer life data. Life data analysis is conducted based on the statistical model and failure prediction for distribution transformers is analysed. Since frequency of failures as a function of time from life data model varies with different manufacturers and affects the life cycle cost, both life data analysis and net present value concept could be combined to establish an enhanced methodology for life cycle cost estimation of distribution transformer failure. A case study was conducted on sample populations where distribution transformer with similar manufacturer and capacity were grouped together. Results for each transformer group were compared and examined. It was pointed by the results that appropriate modelling and analysis had allowed life cycle cost due to transformer failure to be estimated. Outcomes from the assessment would contribute to transformer life cycle management as one of the factors to consider in the decision making for asset replacement, maintenance and planning.