The Administrative Office of the United States Courts uses time-and-motion techniques to determine a set of judicial input-output coefficients, which vary by case category. These coefficients measure the average judge time that is required in the courtroom to complete a given category of case. A projection is then made of the flow of newly lodged cases, and the coefficients are then applied to calculate the number of judges required to handle the courts' business. This paper refers to this procedure as the "fixed coefficients approach" (FCA). FCA is applied formally or informally by most court administrations. This paper argues that FCA is inappropriate and that expansion of the judiciary will not achieve its objective of controlling the backlog. The FCA is first challenged by arguing that if the FCA succeeds in reducing the backlog by increasing the number of judges, the demand for litigation will increase. Recognizing that court cases are moving more rapidly through the courts, the incentive for litigation will increase, and the backlog will remain virtually unchanged. The second argument against the validity of FCA is that in common with other service providers, judges provide more service when under pressure. This recognition underlies this paper's theory that "pressure induces productivity" (PIP). The author uses data on Israel's courts to measure the PIP theory. The data analysis shows that the output of Israel's judiciary, as measured by the number of completed cases, does not vary with judicial inputs as measured by the number of judges. The appointment of additional judges lowers the caseload of existing judges, who then respond by lowering their productivity. The percentage decline in productivity is equal to the percentage increase in the number of judges, implying that the output of the courts remains unchanged. The author offers some suggestions for maintaining the pressure on judges to produce even after more judges have been added. He also discusses issues associated with the quality of justice in relation to productivity. 3 figures and 2 notes