An increase in the number of accidents in the process-industries and the concomitant damage potential is a cause of concern in many countries. In order to control the alarming risk posed by these industries, the United States government has asked each manufacturing facility to carry out a worst-case disaster study and to develop alternatives to control this high risk. Other developed and developing countries such as Canada and India have taken similar measures. Recently Khan and Abbasi (J. Loss Prevent. Process Ind. (2001a) in press) have proposed a maximum credible accident analysis with a maximum credible accident scenario approach, which scores over a worst-case scenario approach for being realistic and reliable. In another effort, Khan and Abbasi (J. Hazard. Mater. (2001b) in press) have developed an efficient and effective algorithm for probabilistic fault tree analysis. These two approaches have been combined to yield a new methodology for a more realistic, reliable, and efficient safety evaluation and the design of risk control measures. The methodology is named SCAP: Safety, Credible Accident, Probabilistic fault tree analysis. The methodology is comprised of four steps of which the last step is a feedback loop. This paper recapitulates this methodology and demonstrates its application to ethylene oxide (EO) plants. The application of SCAP to EO plants identifies five units as risky and needing more safety measures. Further, this study recommends safety measures and demonstrates through SCAP that their implementation lower the risk to an acceptable level. (C) 2002 Elsevier Science Ltd. All rights reserved.