Higher yields in office rent encourage new office development areas in the city as well as stimulating cash flow to real estate investment and invigorating the dynamics of the local economy. It is well established that mathematical rent prediction models are highly susceptible to spatial differences, and that have to be envisaged on the basis of local determinants. As a consequence, it is inevitable that, from the extensive number of parameters affecting the office rent, a scale should be constructed to observe the parameter influences particular to a region. Traditional hedonic theory based on multiple linear regression is incapable of treating the large number of parameters, mainly due to multicolllinearity problem. Thus, principal component analysis has been first..run on parameters to group correlated parameters into unrelated factor groups. Following the construction of factors, factor analysis was then utilized to determine the factor loadings and the corresponding influence levels of the office rent determinants in Istanbul. Analytical results indicate that a group of parameters (Factor 5 in paper) affecting the reselling value of the building, the vacancy rate, and the percentage of common spaces in the office building are the most highly rated determinants. Upon comparison with previously conducted studies elsewhere around the globe, only the vacancy rate can be confirmed as the most influential determinant being independent from any regional differences.