Conventional time-based inspection of power transformers does not reflect differences in the condition and risk of individual units when inspection intervals and items are set. This paper proposes a risk-based inspection planning framework that determines the inspection intervals and items of 154 kV power transformers using statistical risk curves and a mapping between failure modes and inspection items derived from failure mode and effects analysis (FMEA). The asset-level probability of failure is obtained from a two-parameter Weibull distribution and apportioned to the winding, bushing, and on-load tap changer (OLTC) according to their failure contributions, and the consequence of failure is evaluated in cost terms for the reliability, financial, safety, and environmental aspects. The risk curve is updated with inspection results; the next inspection time is the year in which the updated risk reaches the next reference risk, and the inspection items follow a grade based on the annual risk increment. Transformers selected in the same year are prioritized by transformer-level risk within the available budget. A scenario-based case study of five transformers analyzes how the inspection times and items change under different condition-change settings and compares the number of inspections, total inspection cost, and present value with time-based inspection. The inspection assignments and unassigned unit-years of the two approaches are also compared under the same budget constraint.